Graphics system having a super-sampled sample buffer with generation of output pixels using selective adjustment of filtering for implementation of display effects

ABSTRACT

A computer graphics system that utilizes a super-sampled sample buffer and a programmable sample-to-pixel calculation unit for refreshing the display, wherein the graphics system may adjust filtering to reduce artifacts or implement display effects. In one embodiment, the graphics system may have a graphics processor, a super-sampled sample buffer, and a sample-to-pixel calculation unit. The graphics processor renders a plurality of samples and stores them into a sample buffer. The sample-to-pixel calculation unit reads the samples from the super-sampled sample buffer and filters or convolves the samples into respective output pixels which are then provided to refresh the display. The sample-to-pixel calculation unit may selectively adjust the filtering of stored samples to reduce artifacts, e.g., is operable to selectively adjust the filtering of stored samples in neighboring frames to reduce artifacts between the neighboring frames. The filter adjustment may be applied where the sample-to-pixel calculation unit generates output pixels at the same rate as the graphics processor rendering samples to the sample buffer, or at a different (e.g., higher) rate than the render rate. The sample-to-pixel calculation unit is operable to adjust filtering of stored samples to implement a display effect, such as panning, zooming, rotation, or moving scenes, among others. The sample-to-pixel calculation unit may also selectively adjust the filtering of stored samples on a fractional-pixel boundary.

CONTINUATION DATA

This application is a continuation-in-part of co-pending application Ser. No. 09/251,453 titled “Graphics System With Programmable Real-Time Sample Filtering”, filed on Feb. 17, 1999, whose inventors are Michael F. Deering, David Naegle, and Scott Nelson, which claims the benefit of U.S. Provisional Application No. 60/074,836 filed Feb. 17, 1998.

BACKGROUND OF THE INVENTION

1. Field of the Invention

This invention relates generally to the field of computer graphics and, more particularly, to high performance graphics systems.

2. Description of the Related Art

A computer system typically relies upon its graphics system for producing visual output on the computer screen or display device. Early graphics systems were only responsible for taking what the processor produced as output and displaying it on the screen. In essence, they acted as simple translators or interfaces. Modern graphics systems, however, incorporate graphics processors with a great deal of processing power. They now act more like coprocessors rather than simple translators. This change is due to the recent increase in both the complexity and amount of data being sent to the display device. For example, modern computer displays have many more pixels, greater color depth, and are able to display more complex images with higher refresh rates than earlier models. Similarly, the images displayed are now more complex and may involve advanced techniques such as anti-aliasing and texture mapping.

As a result, without considerable processing power in the graphics system, the CPU would spend a great deal of time performing graphics calculations. This could rob the computer system of the processing power needed for performing other tasks associated with program execution and thereby dramatically reduce overall system performance. With a powerful graphics system, however, when the CPU is instructed to draw a box on the screen, the CPU is freed from having to compute the position and color of each pixel. Instead, the CPU may send a request to the video card stating “draw a box at these coordinates.” The graphics system then draws the box, freeing the processor to perform other tasks.

Generally, a graphics system in a computer (also referred to as a graphics system) is a type of video adapter that contains its own processor to boost performance levels. These processors are specialized for computing graphical transformations, so they tend to achieve better results than the general-purpose CPU used by the computer system. In addition, they free up the computer's CPU to execute other commands while the graphics system is handling graphics computations. The popularity of graphical applications, and especially multimedia applications, has made high performance graphics systems a common feature of computer systems. Most computer manufacturers now bundle a high performance graphics system with their systems.

Since graphics systems typically perform only a limited set of functions, they may be customized and therefore are far more efficient at graphics operations than the computer's general-purpose central processor. While early graphics systems were limited to performing two-dimensional (2D) graphics, their functionality has increased to support three-dimensional (3D) wire-frame graphics, 3D solids, and now includes support for three-dimensional (3D) graphics with textures and special effects such as advanced shading, fogging, alpha-blending, and specular highlighting.

The processing power of 3D graphics systems has been improving at a breakneck pace. A few years ago, shaded images of simple objects could only be rendered at a few frames per second, while today's systems support rendering of complex objects at 60 Hz or higher. At this rate of increase, in the not too distant future, graphics systems will literally be able to render more pixels than a single human's visual system can perceive. While this extra performance may be useable in multiple-viewer environments, it may be wasted in more common primarily single-viewer environments. Thus, a graphics system is desired which is capable of matching the variable nature of the human resolution system (i.e., capable of putting the quality where it is needed or most perceivable).

While the number of pixels is an important factor in determining graphics system performance, another factor of equal import is the quality of the image. For example, an image with a high pixel density may still appear unrealistic if edges within the image are too sharp or jagged (also referred to as “aliased”). One well-known technique to overcome these problems is anti-aliasing. Anti-aliasing involves smoothing the edges of objects by shading pixels along the borders of graphical elements. More specifically, anti-aliasing entails removing higher frequency components from an image before they cause disturbing visual artifacts. For example, anti-aliasing may soften or smooth high contrast edges in an image by forcing certain pixels to intermediate values (e.g., around the silhouette of a bright object superimposed against a dark background).

Another visual effect used to increase the realism of computer images is alpha blending. Alpha blending is a technique that controls the transparency of an object, allowing realistic rendering of translucent surfaces such as water or glass. Another effect used to improve realism is fogging. Fogging obscures an object as it moves away from the viewer. Simple fogging is a special case of alpha blending in which the degree of alpha changes with distance so that the object appears to vanish into a haze as the object moves away from the viewer. This simple fogging may also be referred to as “depth cueing” or atmospheric attenuation, i.e., lowering the contrast of an object so that it appears less prominent as it recedes. More complex types of fogging go beyond a simple linear function to provide more complex relationships between the level of translucence and an object's distance from the viewer. Current state of the art software systems go even further by utilizing atmospheric models to provide low-lying fog with improved realism.

While the techniques listed above may dramatically improve the appearance of computer graphics images, they also have certain limitations. In particular, they may introduce their own aberrations and are typically limited by the density of pixels displayed on the display device.

As a result, a graphics system is desired which is capable of utilizing increased performance levels to increase not only the number of pixels rendered but also the quality of the image rendered. In addition, a graphics system is desired which is capable of utilizing increases in processing power to improve the results of graphics effects such as anti-aliasing.

Prior art graphics systems have generally fallen short of these goals. Prior art graphics systems use a conventional frame buffer for refreshing pixel/video data on the display. The frame buffer stores rows and columns of pixels that exactly correspond to respective row and column locations on the display. Prior art graphics system render 2D and/or 3D images or objects into the frame buffer in pixel form, and then read the pixels from the frame buffer during a screen refresh to refresh the display. Thus, the frame buffer stores the output pixels that are provided to the display. To reduce visual artifacts that may be created by refreshing the screen at the same time the frame buffer is being updated, most graphics systems' frame buffers are double-buffered.

To obtain more realistic images, some prior art graphics systems have gone further by generating more than one sample per pixel. As used herein, the term “sample” refers to calculated color information that indicates the color, depth (z), transparency, and potentially other information, of a particular point on an object or image. For example a sample may comprise the following component values: a red value, a green value, a blue value, a z value, and an alpha value (e.g., representing the transparency of the sample). A sample may also comprise other information, e.g., a z-depth value, a blur value, an intensity value, brighter-than-bright information, and an indicator that the sample consists partially or completely of control information rather than color information (i.e., “sample control information”). By calculating more samples than pixels (i.e., super-sampling), a more detailed image is calculated than can be displayed on the display device. For example, a graphics system may calculate four samples for each pixel to be output to the display device. After the samples are calculated, they are then combined or filtered to form the pixels that are stored in the frame buffer and then conveyed to the display device. Using pixels formed in this manner may create a more realistic final image because overly abrupt changes in the image may be smoothed by the filtering process.

These prior art super-sampling systems typically generate a number of samples that are far greater than the number of pixel locations on the display. These prior art systems typically have rendering processors that calculate the samples and store them into a render buffer. Filtering hardware then reads the samples from the render buffer, filters the samples to create pixels, and then stores the pixels in a traditional frame buffer. The traditional frame buffer is typically double-buffered, with one side being used for refreshing the display device while the other side is updated by the filtering hardware. Once the samples have been filtered, the resulting pixels are stored in a traditional frame buffer that is used to refresh the display device. These systems, however, have generally suffered from limitations imposed by the conventional frame buffer and by the added latency caused by the render buffer and filtering. Therefore, an improved graphics system is desired which includes the benefits of pixel super-sampling while avoiding the drawbacks of the conventional frame buffer.

U.S. patent application Ser. No. 09/251,453 titled “Graphics System With Programmable Real-Time Sample Filtering” discloses a computer graphics system that utilizes a super-sampled sample buffer and a sample-to-pixel calculation unit for refreshing the display. The graphics processor generates a plurality of samples and stores them into a sample buffer. The graphics processor preferably generates and stores more than one sample for at least a subset of the pixel locations on the display. Thus, the sample buffer is a super-sampled sample buffer which stores a number of samples that may be far greater than the number of pixel locations on the display. The sample-to-pixel calculation unit is configured to read the samples from the super-sampled sample buffer and filter or convolve the samples into respective output pixels, wherein the output pixels are then provided to refresh the display. The sample-to-pixel calculation unit selects one or more samples and filters them to generate an output pixel. The sample-to-pixel calculation unit may operate to obtain samples and generate pixels which are provided directly to the display with no frame buffer therebetween.

It would be desirable to use this improved graphics architecture to provide further improved display capabilities, including reduced artifacts, such as when the render rate differs from the pixel generation rate, as well as improved display effects, such as panning, zooming and the like, including 2D panning and zooming as well as 3D movement, e.g., position and rotation changes, around a camera's first nodal point.

SUMMARY OF THE INVENTION

The present invention comprises a computer graphics system that utilizes a super-sampled sample buffer and a programmable sample-to-pixel calculation unit for refreshing the display, wherein the graphics system may adjust sample filtering to reduce artifacts or implement display effects. In one embodiment, the graphics system may have a graphics processor, a super-sampled sample buffer, and a sample-to-pixel calculation unit. The graphics processor generates a plurality of samples and stores them into a sample buffer. The graphics processor preferably generates and stores more than one sample for at least a subset of the pixel locations on the display. Thus, the sample buffer is a super-sampled sample buffer which stores a number of samples that, in some embodiments, may be far greater than the number of pixel locations on the display. In other embodiments, the total number of samples may be closer to, equal to, or even less than the total number of pixel locations on the display device, but the samples may be more densely positioned in certain areas and less densely positioned in other areas.

The sample-to-pixel calculation unit is configured to read the samples from the super-sampled sample buffer and filter or convolve the samples into respective output pixels, wherein the output pixels are then provided to refresh the display. The sample-to-pixel calculation unit selects one or more samples and filters them to generate an output pixel. Note the number of samples selected and/or filtered by the sample-to-pixel calculation unit may be one or, in the preferred embodiment, greater than one.

The sample-to-pixel calculation unit may access the samples from the super-sampled sample buffer, perform a filtering operation, and then provide the resulting output pixels directly to the display, preferably in real-time. The graphics system may operate without a conventional frame buffer, i.e., the graphics system may not utilize a conventional frame buffer which stores the actual pixel values that are being refreshed on the display. Note some displays may have internal frame buffers, but these are considered an integral part of the display device, not the graphics system. Thus, the sample-to-pixel calculation units may calculate each pixel for each screen refresh on a real time basis or on an on-the-fly basis.

In one embodiment, the sample-to-pixel calculation unit is operable to adjust the filtering of stored samples to reduce or adjust artifacts, e.g., is operable to selectively adjust the filtering of stored samples in neighboring frames to reduce artifacts between the neighboring frames. For example, the sample-to-pixel calculation unit may select and filter a first set of stored samples to generate first output pixels for display using a first filter, and may later select and filter a second set of stored samples to generate second output pixels for display using a second filter different than the first filter. In one embodiment, the sample-to-pixel calculation unit may selectively adjust the filtering of stored samples in neighboring frames by simulation of various screen effects or display effects, such as panning, zooming and the like, including 2D panning and zooming as well as 3D movement, e.g., position and rotation changes, around a camera's first nodal point, for reduced artifacts.

The sample-to-pixel calculation unit preferably selectively adjusts center locations (centers) in the sample buffer where the filter (e.g., a convolution filter) is applied during filtering of stored samples to reduce artifacts. The center locations where the convolution filter is applied correspond to the centers of the output pixels being generated. The sample-to-pixel calculation unit includes address generator logic for generating addresses corresponding to the center locations, wherein the convolution filter is applied to these center locations in generating output pixels for display. The address generator logic is programmable to generate addresses at selected sub-pixel positions corresponding to the desired centers. In the preferred embodiment, the beginning sub-pixel position address generated by the address generator logic is programmable, and the pixel step size may remain constant. The sample-to-pixel calculation unit is operable to selectively adjust the center locations where the filter is applied in one or more of the x or y direction, and may adjust the center locations of the filter by a sub-pixel distance. The sample-to-pixel calculation unit may utilize a convolution filter in filtering the samples, or other types of filters.

In this embodiment, the sample buffer may store samples corresponding to an area greater then a viewable area of the display, and one or more samples from outside the (previously) viewable area of the display may be used in generation of output pixels according to the adjusted convolution centers. The graphics system may also be operable to selectively adjust video timing to compensate for the adjustment of the center locations of the convolution filter during filtering of stored samples.

The present invention may be applied where the sample-to-pixel calculation unit generates output pixels at the same rate as the graphics processor rendering samples to the sample buffer. For example, if a current set of stored samples is determined to be similar or identical to a previous set of stored samples that were previously used in generating output pixels in a previous frame, the sample-to-pixel calculation unit may selectively adjust the filtering of the current set of stored samples in a current frame to reduce artifacts. Thus, if a set of stored samples has been previously used in generating first output pixels in a prior frame, the sample-to-pixel calculation unit may selectively adjust the filtering of a similar set (or the same set) of stored samples to generate different pixels in a subsequent frame to reduce artifacts. Thus, in situations where the camera's nodal point remains substantially fixed between neighboring frames, the present invention operates to effectively subtly vary the camera's nodal point to remove any artifacts that may appear between neighboring frames.

The present invention also comprises a graphics system as described above, wherein the sample-to-pixel calculation unit may operate at a different (e.g., higher) rate than the render rate. For example, the sample-to-pixel calculation unit may generate output pixels at a different rate than the graphics processor rendering samples to the sample buffer, e.g., the graphics processor is operable to render the plurality of samples to the sample buffer at a first rate, and the sample-to-pixel calculation unit is operable to generate output pixels at a second greater rate. This allows the convolve pipeline in the sample-to-pixel calculation unit to operate on-the-fly independent of the render rate. In this system, the sample-to-pixel calculation unit is operable to selectively adjust the filtering of stored samples between neighboring frames as described above to reduce artifacts. Thus, where a first set of stored samples is determined to have been previously used in generating output pixels in a prior frame, the sample-to-pixel calculation unit is operable to selectively adjust the filtering of the first set of stored samples in a current (or subsequent) frame to reduce artifacts. Thus, the samples may be created once, and then convolved two or more times with different filters to remove artifacts, until the graphics processor renders new samples into the sample buffer.

In another embodiment, the sample-to-pixel calculation unit is operable to adjust filtering of stored samples to implement a display effect. More particularly, the sample-to-pixel calculation unit is operable to selectively adjust the filtering of stored samples in neighboring frames to implement a display effect between the neighboring frames. The display effect may comprise panning, zooming, rotation, or moving scenes, among others, including 2D panning and zooming as well as 3D movement, e.g., position and rotation changes, around a camera's first nodal point

In this embodiment, the sample buffer may store samples corresponding to an area greater then a viewable area of the display, and one or more samples from outside the (previously) viewable area of the display may be used to implement the display effect. The sample-to-pixel calculation unit may adjust filtering by adjusting one or more of the positions (centers) of pixels, the radius of the filter, and the pitch between pixels. The sample-to-pixel calculation unit may adjust filtering of stored samples to implement the display effect on a fractional-pixel boundary. For example, the sample-to-pixel calculation unit may selectively adjust the filtering of stored samples in neighboring frames to effect panning or zooming between the neighboring frames on a fractional-pixel boundary.

One benefit of this invention is smoother panning or zooming when the samples are being rendered at a lesser rate than the convolve. For example, assume a situation where the camera is panning in a certain direction, or zooming in or out, and the samples are being rendered at half the rate of the convolve. In this instance, two convolve operations may be performed on the same data, and then a jump to the next pan position occurs in the next rendered frame. According to the present invention, the sample-to-pixel calculation unit may operate to adjust the convolution centers (e.g., move 10.5 pixels to the right) in the second convolution cycle to effect the pan operation, even though new data corresponding to the pan has not yet been rendered. Thus, if a display effect is desired, and if a first set of stored samples has been previously used in generating output pixels in a prior frame, the sample-to-pixel calculation unit is operable to selectively adjust the filtering of the first set of stored samples in a subsequent frame to implement the display effect in the subsequent frame.

A software program embodied on a computer medium and a method for operating a graphics subsystem are also contemplated. In one embodiment, the method comprises first calculating a plurality of sample locations, and then generating a sample for each sample pixel location. The samples may then be stored (e.g., into the super-sampled sample buffer). The sample locations may be specified according to any number of positioning or spacing schemes. The stored samples may then be selected and filtered to form output pixels, which are provided in real time directly to the display, preferably without being stored in a traditional frame buffer. The generation of output pixels may include selectively adjusting the filtering of stored samples to reduce artifacts or to generate display effects. The generation of output pixels may also operate at the same or a different rate than the render rate.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing, as well as other objects, features, and advantages of this invention may be more completely understood by reference to the following detailed description when read together with the accompanying drawings in which:

FIG. 1 illustrates one embodiment of a computer system that includes one embodiment of a graphics system;

FIG. 1A illustrates a computer network comprising at least one server computer and one or more client computers, wherein the client computers include one embodiment of a graphics system;

FIG. 2 is a simplified block diagram of the computer system of FIG. 1;

FIG. 3 is a block diagram illustrating more details of one embodiment of the graphics system of FIG. 1;

FIG. 4 illustrates traditional pixel calculation;

FIG. 5A illustrates one embodiment of super-sampling;

FIG. 5B illustrates a random distribution of samples;

FIG. 6 illustrates details of one embodiment of a graphics system having one embodiment of a variable resolution super-sampled sample buffer;

FIG. 7 illustrates details of another embodiment of a graphics system having one embodiment of a variable resolution super-sampled sample buffer;

FIG. 8 illustrates details of three different embodiments of sample positioning schemes;

FIG. 9 illustrates details of one embodiment of a sample positioning scheme;

FIG. 10 illustrates details of another embodiment of a sample positioning scheme;

FIG. 11 illustrates details of method of converting samples to pixels in parallel;

FIG. 11A illustrates more details of the embodiment from FIG. 11;

FIG. 11B illustrates details of one embodiment of a method for dealing with boundary conditions;

FIG. 12 is a flowchart illustrating one embodiment of a method for drawing samples into a super-sampled sample buffer;

FIG. 12A illustrates one embodiment for coding triangle vertices;

FIG. 13 illustrates one embodiment of a method for calculating pixels from samples;

FIG. 14 illustrates details of one embodiment of a pixel convolution for an example set of samples;

FIG. 15 is a flowchart diagram illustrating adjustment of filtering for a frame of pixels;

FIG. 16A illustrates a first filtering method for samples, wherein the convolution centers are centered on the bins;

FIG. 16B illustrates a portion of the pixel image produced by the samples using the first filtering method of FIG. 16A, wherein the pixel image includes an artifact (an aliased line);

FIG. 17A illustrates a second filtering method for samples, wherein the convolution centers are shifted leftward relative to the bins;

FIG. 17B illustrates a portion of the pixel image produced by the samples using the second filtering method of FIG. 17A, wherein the pixel image does not include the artifact of FIG. 16B;

FIG. 18 illustrates a first filtering method for samples, wherein the convolution centers are centered on the bins;

FIG. 19 illustrates a second filtering method for samples to implement a zooming display effect, wherein the convolution centers are spaced a greater distance apart and the filter radius has been increased; and

FIG. 20 is a flowchart diagram illustrating generation of display effects.

While the invention is susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the drawings and will herein be described in detail. It should be understood, however, that the drawings and detailed description thereto are not intended to limit the invention to the particular form disclosed, but on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the present invention as defined by the appended claims.

DETAILED DESCRIPTION OF SEVERAL EMBODIMENTS

Incorporation by Reference

U.S. patent application Ser. No. 09/251,453 titled “Graphics System With Programmable Real-Time Sample Filtering”, filed on Feb. 17, 1999, whose inventors are Michael F. Deering, David Naegle, and Scott Nelson, is hereby incorporated by reference as though fully and completely set forth herein.

Computer System—FIG. 1

Referring now to FIG. 1, one embodiment of a computer system 80 that includes a three-dimensional (3-D) graphics system is shown. The 3-D graphics system may be comprised in any of various systems, including a computer system, network PC, Internet appliance, a television, including HDTV systems and interactive television systems, personal digital assistants (PDAs), and other devices which display 2D and or 3D graphics, among others.

As shown, the computer system 80 comprises a system unit 82 and a video monitor or display device 84 coupled to the system unit 82. The display device 84 may be any of various types of display monitors or devices (e.g., a CRT, LCD, gas-plasma display, digital mirror display (DMD), or reflective silicon LCD). Various input devices may be connected to the computer system, including a keyboard 86 and/or a mouse 88, or other input device (e.g., a trackball, digitizer, tablet, six-degree of freedom input device, head tracker, eye tracker, data glove, body sensors, etc.). Application software may be executed by the computer system 80 to display 3-D graphical objects on display device 84.

As described further below, the 3-D graphics system in computer system 80 includes a super-sampled sample buffer with a programmable sample-to-pixel calculation unit to improve the quality and realism of images displayed on display device 84. The sample-to-pixel calculation unit may include a filter or convolve pipeline or other hardware for generating pixels in response to samples in the sample buffer. The sample-to-pixel calculation unit may operate to obtain samples from the sample buffer and generate pixels which are provided directly to the display. The sample-to-pixel calculation unit may operate in a “real-time” or “on-the-fly” fashion.

As used herein the terms “filter” and “convolve” are used interchangeably and refer to mathematically manipulating one or more samples to generate a pixel (e.g., by averaging, by applying a convolution function, by summing, by applying a filtering function, by weighting the samples and then manipulating them, by applying a randomized function, etc.).

As used herein, the term “real-time” refers to a function that is performed at or near the display device's refresh rate. “On-the-fly” means at, near, or above the human visual system's perception capabilities for motion fusion (how often a picture must be changed to give the illusion of continuous motion) and flicker fusion (how often light intensity must be changed to give the illusion of continuous). These concepts are further described in the book “Spatial Vision” by Russel L. De Valois and Karen K. De Valois, Oxford University Press, 1988.

According to the present invention, the sample-to-pixel calculation unit may operate to selectively adjust the filtering of stored samples to reduce artifacts or to generate display effects. The generation of output pixels may also operate at the same or a different rate than the render rate of samples being calculated and stored in the sample buffer according to the present invention.

Computer Network—FIG. 1A

Referring now to FIG. 1A, a computer network 500 is shown comprising at least one server computer 502 and one or more client computers 506A-N. (In the embodiment shown in FIG. 1A, client computers 506A-B are depicted). One or more of the client systems may be configured similarly to computer system 80, with each having one or more graphics systems 112 as described above. Server 502 and client(s) 506 may be joined through a variety of connections 504, such as a local-area network (LAN), a wide-area network (WAN), or an Internet connection. In one embodiment, server 502 may store and transmit 3-D geometry data (which may be compressed) to one or more of clients 506. The clients 506 receive the compressed 3-D geometry data, decompress it (if necessary) and then render the geometry data. The rendered image is then displayed on the client's display device. The clients render the geometry data and display the image using super-sampled sample buffer and real-time filter techniques described herein. In another embodiment, the compressed 3-D geometry data may be transferred between client computers 506.

Computer System Block Diagram—FIG. 2

Referring now to FIG. 2, a simplified block diagram illustrating the computer system of FIG. 1 is shown. FIG. 2 may also illustrate the computers 506A, 506B, or 502. Elements of the computer system that are not necessary for an understanding of the present invention are not shown for convenience. As shown, the computer system 80 includes a central processing unit (CPU) 102 coupled to a high-speed memory bus or system bus 104 also referred to as the host bus 104. A system memory 106 may also be coupled to high-speed bus 104.

Host processor 102 may comprise one or more processors of varying types, e.g., microprocessors, multi-processors and CPUs. The system memory 106 may comprise any combination of different types of memory subsystems, including random access memories, (e.g., static random access memories or “SRAMs”, synchronous dynamic random access memories or “SDRAMs”, and Rambus dynamic access memories or “RDRAM”, among others) and mass storage devices. The system bus or host bus 104 may comprise one or more communication or host computer buses (for communication between host processors, CPUs, and memory subsystems) as well as specialized subsystem buses.

A 3-D graphics system or graphics system 112 according to the present invention is coupled to the high-speed memory bus 104. The 3-D graphics system 112 may be coupled to the bus 104 by, for example, a crossbar switch or other bus connectivity logic. It is assumed that various other peripheral devices, or other buses, may be connected to the high-speed memory bus 104. It is noted that the 3-D graphics system may be coupled to one or more of the buses in computer system 80 and/or may be coupled to various types of buses. In addition, the 3D graphics system may be coupled to a communication port and thereby directly receive graphics data from an external source, e.g., the Internet or a network. As shown in the figure, display device 84 is connected to the 3-D graphics system 112 comprised in the computer system 80.

Host CPU 102 may transfer information to and from the graphics system 112 according to a programmed input/output (I/O) protocol over host bus 104. Alternately, graphics system 112 may access the memory subsystem 106 according to a direct memory access (DMA) protocol or through intelligent bus mastering.

A graphics application program conforming to an application programming interface (API) such as OpenGL or Java 3D may execute on host CPU 102 and generate commands and data that define a geometric primitive (graphics data) such as a polygon for output on display device 84. As defined by the particular graphics interface used, these primitives may have separate color properties for the front and back surfaces. Host processor 102 may transfer these graphics data to memory subsystem 106. Thereafter, the host processor 102 may operate to transfer the graphics data to the graphics system 112 over the host bus 104. In another embodiment, the graphics system 112 may read in geometry data arrays over the host bus 104 using DMA access cycles. In yet another embodiment, the graphics system 112 may be coupled to the system memory 106 through a direct port, such as a version of the Advanced Graphics Port (AGP) promulgated by Intel Corporation.

The graphics system may receive graphics data from any of various sources, including the host CPU 102 and/or the system memory 106, other memory, or from an external source such as a network, e.g., the Internet, or from a broadcast medium, e.g., television, or from other sources.

As will be described below, graphics system 112 may be configured to allow more efficient microcode control, which results in increased performance for handling of incoming color values corresponding to the polygons generated by host processor 102. Note while graphics system 112 is depicted as part of computer system 80, graphics system 112 may also be configured as a stand-alone device (e.g., with its own built-in display). Graphics system 112 may also be configured as a single chip device or as part of a system-on-a-chip or a multi-chip module.

Graphics System—FIG. 3

Referring now to FIG. 3, a block diagram illustrating details of one embodiment of graphics system 112 is shown. As shown in the figure, graphics system 112 may comprise one or more graphics processors 90, one or more super-sampled sample buffers 162, and one or more sample-to-pixel calculation units 170A-D. Graphics system 112 may also comprise one or more digital-to-analog converters (DACs) 178A-B. Graphics processor 90 may be any suitable type of high performance processor (e.g., specialized graphics processors or calculation units, multimedia processors, DSPs, or general purpose processors). In one embodiment, graphics processor 90 may comprise one or more rendering units 150A-D. In the embodiment shown, however, graphics processor 90 also comprises one or more control units 140, one or more data memories 152A-D, and one or more schedule units 154. Sample buffer 162 may comprises one or more sample memories 160A-160N as shown in the figure.

A. Control Unit

Control unit 140 operates as the interface between graphics system 112 and computer system 80 by controlling the transfer of data between graphics system 112 and computer system 80. In embodiments of graphics system 112 that comprise two or more rendering units 150A-D, control unit 140 may also divide the stream of data received from computer system 80 into a corresponding number of parallel streams that are routed to the individual rendering units 150A-D. The graphics data may be received from computer system 80 in a compressed form. This may advantageously reduce the bandwidth requirements between computer system 80 and graphics system 112. In one embodiment, control unit 140 may be configured to split and route the data stream to rendering units 150A-D in compressed form.

The graphics data may comprise one or more graphics primitives. As used herein, the term graphics primitive includes polygons, parametric surfaces, splines, NURBS (non-uniform rational B-splines), sub-divisions surfaces, fractals, volume primitives, and particle systems. These graphics primitives are described in detail in the text book entitled “Computer Graphics: Principles and Practice” by James D. Foley, et al., published by Addison-Wesley Publishing Co., Inc., 1996. Note polygons are referred to throughout this detailed description for simplicity, but the embodiments and examples described may also be used with graphics data comprising other types of graphics primitives.

B. Rendering Units

Rendering units 150A-D (also referred to herein as draw units) are configured to receive graphics instructions and data from control unit 140 and then perform a number of functions, depending upon the exact implementation. For example, rendering units 150A-D may be configured to perform decompression (if the data is compressed), transformation, clipping, lighting, texturing, depth cueing, transparency processing, set-up, and screen space rendering of various graphics primitives occurring within the graphics data. Each of these features is described separately below.

Depending upon the type of compressed graphics data received, rendering units 150A-D may be configured to perform arithmetic decoding, run-length decoding, Huffman decoding, and dictionary decoding (e.g., LZ77, LZSS, LZ78, and LZW). In another embodiment, rendering units 150A-D may be configured to decode graphics data that has been compressed using geometric compression. Geometric compression of 3D graphics data may achieve significant reductions in data size while retaining most of the image quality. Two methods for compressing and decompressing 3D geometry are described in U.S. Pat. No. 5,793,371, application Ser. No. 08/511,294, (filed on Aug. 4, 1995, entitled “Method And Apparatus For Geometric Compression of Three-Dimensional Graphics Data,” and U.S. patent application Ser. No. 09/095,777, filed on Jun. 11, 1998, entitled “Compression of Three-Dimensional Geometry Data Representing a Regularly Tiled Surface Portion of a Graphical Object,”. In embodiments of graphics system 112 that support decompression, the graphics data received by each rendering unit 150 is decompressed into one or more graphics “primitives” which may then be rendered. The term primitive refers to components of objects that define its shape (e.g., points, lines, triangles, polygons in two or three dimensions, polyhedra, or free-form surfaces in three dimensions). Rendering units 150 may be any suitable type of high performance processor (e.g., specialized graphics processors or calculation units, multimedia processors, DSPs, or general purpose processors).

Transformation refers to manipulating an object and includes translating the object (i.e., moving the object to a different location), scaling the object (i.e., stretching or shrinking), and rotating the object (e.g., in three-dimensional space, or “3-space”).

Clipping refers to defining the limits of the displayed image (i.e., establishing a clipping region, usually a rectangle) and then not rendering or displaying pixels that fall outside those limits.

Lighting refers to calculating the illumination of the objects within the displayed image to determine what color and or brightness each individual object will have. Depending upon the shading algorithm being used (e.g., constant, Gourand, or Phong), lighting may be evaluated at a number of different locations. For example, if constant shading is used (i.e., each pixel of a polygon has the same lighting), then the lighting need only be calculated once per polygon. If Gourand shading is used, then the lighting is calculated once per vertex. Phong shading calculates the lighting on a per-pixel basis.

Set-up refers to mapping primitives to a three-dimensional viewport. This involves translating and transforming the objects from their original “world-coordinate” system to the established viewport's coordinates. This creates the correct perspective for three-dimensional objects displayed on the screen.

Screen-space rendering refers to the calculations performed to actually calculate the data used to generate each pixel that will be displayed. In prior art systems, each pixel is calculated and then stored in a frame buffer. The contents of the frame buffer are then output to the display device to create the final image. In the embodiment of graphics system 112 shown in the figure, however, rendering units 150A-D calculate “samples” instead of actual pixel data. This allows rendering units 150A-D to “super-sample” or calculate more than one sample per pixel. Super-sampling is described in greater detail below. The rendering units 150A-D may also generate a greater area of samples than the viewable area of the display 84 for various effects such as panning and zooming. Note that rendering units 150A-B may comprises a number of smaller functional units, e.g., a separate set-up/decompress unit and a lighting unit.

More details on super-sampling are discussed in the following books: “Principles of Digital Image Synthesis” by Andrew Glassner, 1995, Morgan Kaufman Publishing (Volume 1); and “Renderman Companion:” by Steve Upstill, 1990, Addison Wesley Publishing.

C. Data Memories

Each rendering unit 150A-D may be coupled to an instruction and data memory 152A-D. In one embodiment, each data memory 152A-D may be configured to store both data and instructions for rendering units 150A-D. While implementations may vary, in one embodiment each data memory 152A-D may comprise two 8 MByte SDRAMs providing a total of 16 MBytes of storage for each rendering unit 150A-D. In another embodiment, RDRAMs (Rambus DRAMs) may be used to support the decompression and set-up operations of each rendering unit, while SDRAMs may be used to support the draw functions of rendering units 150A-D.

D. Schedule Unit

Schedule unit 154 may be coupled between the rendering units 150A-D and the sample memories 160A-N. Schedule unit 154 is configured to sequence the completed samples and store them in sample memories 160A-N. Note in larger configurations, multiple schedule units 154 may be used in parallel. In one embodiment, schedule unit 154 may be implemented as a crossbar switch.

E. Sample Memories

Super-sampled sample buffer 162 comprises sample memories 160A-160N, which are configured to store the plurality of samples generated by the rendering units. As used herein, the term “sample buffer” refers to one or more memories which store samples. As previously noted, one or more samples are filtered to form output pixels (i.e., pixels to be displayed on a display device). The number of samples stored may be greater than, equal to, or less than the total number of pixels output to the display device to refresh a single frame. Each sample may correspond to one or more output pixels. As used herein, a sample “corresponds” to an output pixel when the sample's information contributes to final output value of the pixel. Note, however, that some samples may contribute zero to their corresponding output pixel after filtering takes place. Also, some samples may be rendered and stored in the sample buffer which are outside the viewable area of the display device 84, wherein these samples may be used for various display effects such as panning and zooming.

Stated another way, the sample buffer stores a plurality of samples that have positions that correspond to locations in screen space on the display, i.e., the samples contribute to one or more output pixels on the display. The number of stored samples may be greater than the number of pixel locations, and more than one sample may be combined in the convolution (filtering) process to generate a particular output pixel displayed on the display device. Any given sample may contribute to one or more output pixels.

Sample memories 160A-160N may comprise any of a number of different types of memories (e.g., SDRAMs, SRAMs, RDRAMs, 3DRAMs, or next-generation 3DRAMs) in varying sizes. In one embodiment, each schedule unit 154 is coupled to four banks of sample memories, wherein each bank comprises four 3DRAM-64 memories. Together, the 3DRAM-64 memories may form a 116-bit deep super-sampled sample buffer that stores multiple samples per pixel. For example, in one embodiment, each sample memory 160A-160N may store up to sixteen samples per pixel.

3DRAM-64 memories are specialized memories configured to support full internal double buffering with single buffered Z in one chip. The double buffered portion comprises two RGBX buffers, wherein X is a fourth channel that can be used to store other information (e.g., alpha). 3DRAM-64 memories also have a lookup table that takes in window ID information and controls an internal 2-1 or 3-1 multiplexer that selects which buffer's contents will be output. 3DRAM-64 memories are next-generation 3DRAM memories that may soon be available from Mitsubishi Electric Corporation's Semiconductor Group. In one embodiment, four chips used in combination are sufficient to create a double-buffered 1280×1024 super-sampled sample buffer. Since the memories are internally double-buffered, the input pins for each of the two frame buffers in the double-buffered system are time multiplexed (using multiplexers within the memories). The output pins may similarly be time multiplexed. This allows reduced pin count while still providing the benefits of double buffering. 3DRAM-64 memories further reduce pin count by not having z output pins. Since z comparison and memory buffer selection is dealt with internally, this may simplify sample buffer 162 (e.g., using less or no selection logic on the output side). Use of 3DRAM-64 also reduces memory bandwidth since information may be written into the memory without the traditional process of reading data out, performing a z comparison, and then writing data back in. Instead, the data may be simply written into the 3DRAM-64, with the memory performing the steps described above internally.

However, in other embodiments of graphics system 112, other memories (e.g., SDRAMs, SRAMs, RDRAMs, or current generation 3DRAMs) may be used to form sample buffer 162.

Graphics processor 90 may be configured to generate a plurality of sample positions according to a particular sample positioning scheme (e.g., a regular grid, a perturbed regular grid, etc.). Alternatively, the sample positions (or offsets that are added to regular grid positions to form the sample positions) may be read from a sample position memory (e.g., a RAM/ROM table). Upon receiving a polygon that is to be rendered, graphics processor 90 determines which samples fall within the polygon based upon the sample positions. Graphics processor 90 renders the samples that fall within the polygon and stores rendered samples in sample memories 160A-N. Note as used herein the terms render and draw are used interchangeable and refer to calculating color values for samples. Depth values, alpha values, and other per-sample values may also be calculated in the rendering or drawing process.

F. Sample-to-pixel Calculation Units

Sample-to-pixel calculation units 170A-D may be coupled between sample memories 160A-N and DACs 178A-B. Sample-to-pixel calculation units 170A-D are configured to read selected samples from sample memories 160A-N and then perform a convolution (e.g., a filtering and weighting function or a low pass filter) on the samples to generate the output pixel values which are output to DACs 178A-B. The sample-to-pixel calculation units 170A-D may be programmable to allow them to perform different filter functions at different times, depending upon the type of output desired. In one embodiment, the sample-to-pixel calculation units 170A-D may implement a 5×5 super-sample reconstruction band-pass filter to convert the super-sampled sample buffer data (stored in sample memories 160A-N) to single pixel values. In other embodiments, calculation units 170A-D may filter a selected number of samples to calculate an output pixel. The filtered samples may be multiplied by a variable weighting factor that gives more or less weight to samples having positions close to the center of the pixel being calculated. Other filtering functions may also be used either alone or in combination, e.g., tent filters, circular and elliptical filters, Mitchell filters, band pass filters, sync function filters, etc.

Sample-to-pixel calculation units 170A-D may also be configured with one or more of the following features: color look-up using pseudo color tables, direct color, inverse gamma correction, filtering of samples to pixels, and conversion of pixels to non-linear light space. Other features of sample-to-pixel calculation units 170A-D may include programmable video timing generators, programmable pixel clock synthesizers, color space converters, and crossbar functions. Once the sample-to-pixel calculation units have manipulated the timing and color of each pixel, the pixels are output to DACs 178A-B.

In one embodiment, the sample-to-pixel calculation unit is operable to adjust the filtering of stored samples to reduce artifacts, e.g., is operable to selectively adjust the filtering of stored samples in neighboring frames to reduce artifacts between the neighboring frames. The filtering may be adjusted by adjusting the center locations where the filter is applied, e.g., adjusting the locations of the convolution centers where pixels are generated relative to a previous frame. This adjustment of filtering of stored samples may operate to reduce artifacts, or reduce visible artifacts, e.g., simply distribute artifacts to different locations in the image whereby they are less perceptible to a human.

In one embodiment, the sample-to-pixel calculation units 170A-D each include address generator logic for generating addresses corresponding to the center locations (centers) in the sample buffer where the convolution filter is applied, wherein the convolution filter is applied to these centers in the sample buffer in generating output pixels for display. The address generator logic is programmable to generate addresses at selected sub-pixel positions corresponding to the desired centers. In the preferred embodiment, the beginning sub-pixel position address generated by the address generator logic is programmable, and the pixel step size may remain constant.

The present invention may be applied where the sample-to-pixel calculation unit generates output pixels at the same rate as the graphics processor rendering samples to the sample buffer, or where the sample-to-pixel calculation unit operates at a different (e.g., higher) rate than the render rate.

In another embodiment of the present invention, the sample-to-pixel calculation unit is operable to adjust filtering of stored samples to implement a display effect, such as panning, zooming, rotation, or moving scenes, among others. This selective adjustment of the filtering of stored samples to reduce artifacts or generate display effects is discussed further below with respect to FIGS. 15-20.

G. DACs

DACs 178A-B operate as the final output stage of graphics system 112. The DACs 178A-B serve to translate the digital pixel data received from cross units 174A-B into analog video signals that are then sent to the display device. Note in one embodiment DACs 178A-B may be bypassed or omitted completely in order to output digital pixel data in lieu of analog video signals. This may be useful when display device 84 is based on a digital technology (e.g., an LCD-type display or a digital micro-mirror display).

As shown, a programmable clock unit 182 operates to provide one or more clocking signals (including a pixel clock) to each of the DACs 178A-B. On each rising edge of the pixel clock, the DACs 178A-B latch the output pixel value(s) into the DACs 178A-B for output of a corresponding analog signal to the display.

When the sample-to-pixel calculation unit horizontally or vertically adjusts the convolution centers in a frame relative to a previous frame as mentioned above, the sample-to-pixel calculation unit also operates to shift or adjust the phase of the pixel clock provided to the DACs 178A-B. This is necessary, due to the adjustment of the convolution centers in a frame relative to a previous frame, to prevent a noticeable “jiggling” of the image. In general, a shift of the convolution centers by a fraction of a pixel directly correlates with a shift in timing by a corresponding amount. The adjustment of video timing to offset the convolution center adjustment in pixel filtering is discussed further below.

In a graphics system where digital pixels are output to the display, the graphics system includes output elements or devices which receive the programmable pixel clock, wherein the output elements do not include digital to analog conversion circuitry.

Super-Sampling—FIGS. 4-5

FIG. 4 illustrates an example of traditional, non-super-sampled pixel value calculation. Each pixel has exactly one data point calculated for it, and the single data point is located at the center of the pixel. For example, only one data point (i.e., sample 74) contributes to value of pixel 70.

Turning now to FIG. 5A, an example of one embodiment of super-sampling is illustrated. In this embodiment, a number of samples are calculated. The number of samples may be related to the number of pixels or completely independent of the number of pixels. In this example, there are 18 samples distributed in a regular grid across nine pixels. Even with all the samples present in the figure, a simple one to one correlation could be made (e.g., by throwing out all but the sample nearest to the center of each pixel). However, the more interesting case is performing a filtering function on multiple samples to determine the final pixel values. Also, as noted above, a single sample can be used to generate a plurality of output pixels, i.e., sub-sampling.

A circular filter 72 is illustrated in the figure. In this example, samples 74A-B both contribute to the final value of pixel 70. This filtering process may advantageously improve the realism of the image displayed by smoothing abrupt edges in the displayed image (i.e., performing anti-aliasing). Filter 72 may simply average samples 74A-B to form the final value of output pixel 70, or it may increase the contribution of sample 74B (at the center of pixel 70) and diminish the contribution of sample 74A (i.e., the sample farther away from the center of pixel 70). Circular filter 72 is repositioned for each output pixel being calculated so the center of filter 72 coincides with the center position of the pixel being calculated. Other filters and filter positioning schemes are also possible and contemplated.

Turning now to FIG. 5B, another embodiment of super-sampling is illustrated. In this embodiment, however, the samples are positioned randomly. More specifically, different sample positions are selected and provided to graphics processor 90 (and render units 150A-D), which calculate color information to form samples at these different locations. Thus the number of samples falling within filter 72 may vary from pixel to pixel.

Super-Sampled Sample buffer with Real-Time Convolution—FIGS. 6-13

FIG. 6 illustrates one possible configuration for the flow of data through one embodiment of graphics system 112. As the figure shows, geometry data 350 is received by graphics system 112 and used to perform draw process 352. The draw process 352 is implemented by one or more of control unit 140, rendering units 150, memories 152, and schedule unit 154. Geometry data 350 comprises data for one or more polygons. Each polygon comprises a plurality of vertices (e.g., three vertices in the case of a triangle), some of which may be shared. Data such as x, y, and z coordinates, color data, lighting data and texture map information may be included for each vertex.

In addition to the vertex data, draw process 352 (which may be performed by rendering units 150A-D) also receives sample coordinates from a sample position memory 354. In one embodiment, position memory 354 is embodied within rendering units 150A-D. In another embodiment, position memory 354 may be realized as part of texture and render memories 152A-152D, or as a separate memory. Sample position memory 354 is configured to store position information for samples that are calculated in draw process 352 and then stored into super-sampled sample buffer 162. In one embodiment, position memory 354 may be configured to store entire sample addresses. However, this may involve increasing the size of position memory 354. Alternatively, position memory 354 may be configured to store only x- and y-offsets for the samples. Storing only the offsets may use less storage space than storing each sample's entire position. The offsets may be relative to bin coordinates or relative to positions on a regular grid. The sample position information stored in sample position memory 354 may be read by a dedicated sample position calculation unit (not shown) and processed to calculate example sample positions for graphics processor 90. More detailed information on sample position offsets is included below (see description of FIGS. 9 and 10).

In another embodiment, sample position memory 354 may be configured to store a table of random numbers. Sample position memory 354 may also comprise dedicated hardware to generate one or more different types of regular grids. This hardware may be programmable. The stored random numbers may be added as offsets to the regular grid positions generated by the hardware. In one embodiment, the sample position memory may be programmable to access or “unfold” the random number table in a number of different ways. This may allow a smaller table to be used without visual artifacts caused by repeating sample position offsets. In one embodiment, the random numbers may be repeatable, thereby allowing draw process 352 and sample-to-pixel calculation process 360 to utilize the same offset for the same sample without necessarily storing each offset.

As shown in the figure, sample position memory 354 may be configured to store sample offsets generated according to a number of different schemes such as a regular square grid, a regular hexagonal grid, a perturbed regular grid, or a random (stochastic) distribution. Graphics system 112 may receive an indication from the operating system, device driver, or the geometry data 350 that indicates which type of sample positioning scheme is to be used. Thus the sample position memory 354 is configurable or programmable to generate position information according to one or more different schemes. More detailed information on several sample position schemes are described further below (see description of FIG. 8).

In one embodiment, sample position memory 354 may comprise a RAM/ROM that contains stochastic sample points (or locations) for different total sample counts per bin. As used herein, the term “bin” refers to a region or area in screen-space and contains however many samples are in that area (e.g., the bin may be 1×1 pixels in area, 2×2 pixels in area, etc.). The use of bins may simplify the storage and access of samples in sample buffer 162. A number of different bin sizes may be used (e.g., one sample per bin, four samples per bin, etc.). In the preferred embodiment, each bin has an xy-position that corresponds to a particular location on the display. The bins are preferably regularly spaced. In this embodiment the bins' xy-positions may be determined from the bin's storage location within sample buffer 162. The bins' positions correspond to particular positions on the display. In some embodiments, the bin positions may correspond to pixel centers, while in other embodiments the bin positions correspond to points that are located between pixel centers. The specific position of each sample within a bin may be determined by looking up the sample's offset in the RAM/ROM table (the offsets may be stored relative to the corresponding bin position). However, depending upon the implementation, not all bin sizes may have a unique RAM/ROM entry. Some bin sizes may simply read a subset of the larger bin sizes' entries. In one embodiment, each supported size has at least four different sample position scheme variants, which may reduce final image artifacts due to repeating sample positions.

In one embodiment, position memory 354 may store pairs of 8-bit numbers, each pair comprising an x-offset and a y-offset (other possible offsets are also possible, e.g., a time offset, a z-offset, etc.). When added to a bin position, each pair defines a particular position in screen space. The term “screen space” refers generally to the coordinate system of the display device. To improve read times, memory 354 may be constructed in a wide/parallel manner so as to allow the memory to output more than one sample location per clock cycle.

Once the sample positions have been read from sample position memory 354, draw process 352 selects the samples positions that fall within the polygon currently being rendered. Draw process 352 then calculates the z and color information (which may include alpha or other depth of field information and/or blur values) for each of these samples and stores the data into sample buffer 162. In one embodiment, the sample buffer may only single-buffer z values (and perhaps alpha values) while double buffering other sample components such as color. Unlike prior art systems, graphics system 112 may double buffer all samples (although not all sample components may be double-buffered, i.e., the samples may have components that are not double-buffered, or not all samples may be double-buffered). In one embodiment, the samples are stored into sample buffer 162 in bins. In some embodiments, the size of bins, i.e., the quantity of samples within a bin, may vary from frame to frame and may also vary across different regions of display device 84 within a single frame. For example, bins along the edges of display device may comprise only one sample, while bins corresponding to pixels near the center of display device 84 may comprise sixteen samples. Note the area of bins may vary from region to region. The use of bins will be described in greater detail below in connection with FIG. 11.

In parallel and independently of draw process 352, filter process 360 is configured to read samples from sample buffer 162, filter (i.e., filter) them, and then output the resulting output pixel to display device 84. Sample-to-pixel calculation units 170 implement filter process 380. Thus, for at least a subset of the output pixels, the filter process is operable to filter a plurality of samples to produce a respective output pixel. In one embodiment, filter process 360 is configured to: (i) determine the distance from each sample to the center of the output pixel being filtered; (ii) multiply the sample's components (e.g., color and alpha) with a filter value that is a specific (programmable) function of the distance; (iii) sum all the weighted samples that contribute to the output pixel, and (iv) normalize the resulting output pixel. The filter process 360 is described in greater detail below (see description accompanying FIGS. 11, 12, and 14). Note the extent of the filter need not be circular (i.e., it may be a function of x and y instead of the distance), but even if the extent is, the filter need not be circularly symmetrical. The filter's “extent” is the area within which samples can influence the particular pixel being calculated with the filter.

According to the present invention, the sample-to-pixel calculation unit is operable to selectively adjust the filtering of stored samples to reduce artifacts or to provide various display effects, as described further below.

Turning now to FIG. 7, a diagram illustrating an alternate embodiment of graphics system 112 is shown. In this embodiment, two or more sample position memories 354A and 354B are utilized. Thus, the sample position memories 354A-B are essentially double-buffered. If the sample positions are kept the same from frame to frame, then the sample positions may be single buffered. However, if the sample positions may vary from frame to frame, then graphics system 112 may be advantageously configured to double-buffer the sample positions. The sample positions may be double buffered on the rendering side (i.e., memory 354A may be double buffered) and or the filter/convolve side (i.e., memory 354B may be double buffered). Other combinations are also possible. For example, memory 354A may be single-buffered, while memory 354B is doubled buffered. This configuration may allow one side of memory 354B to be used for refreshing (i.e., by filter/convolve process 360) while the other side of memory 354B is used being updated. In this configuration, graphics system 112 may change sample position schemes on a per-frame basis by shifting the sample positions (or offsets) from memory 354A to double-buffered memory 354B as each frame is rendered. Thus, the positions used to calculate the samples (read from memory 354A) are copied to memory 354B for use during the filtering process (i.e., the sample-to-pixel conversion process). Once the position information has been copied to memory 354B, position memory 354A may then be loaded with new sample position offsets to be used for the second frame to be rendered. In this way the sample position information follows the samples from the draw/render process to the filter process.

Yet another alternative embodiment may store tags to offsets with the samples themselves in super-sampled sample buffer 162. These tags may be used to look-up the offset/perturbation associated with each particular sample.

Sample Positioning Schemes

FIG. 8 illustrates a number of different sample positioning schemes. In regular grid positioning scheme 190, each sample is positioned at an intersection of a regularly-spaced grid. Note however, that as used herein the term “regular grid” is not limited to square grids. Other types of grids are also considered “regular” as the term is used herein, including, but not limited to, rectangular grids, hexagonal grids, triangular grids, logarithmic grids, and semi-regular lattices such as Penrose tiling.

Perturbed regular grid positioning scheme 192 is based upon the previous definition of a regular grid. However, the samples in perturbed regular grid scheme 192 may be offset from their corresponding grid intersection. In one embodiment, the samples may be offset by a random angle (e.g., from 0° to 360°) and a random distance, or by random x and y offsets, which may or may not be limited to a predetermined range. The offsets may be generated in a number of ways, e.g., by hardware based upon a small number of seeds, looked up from a table, or by using a pseudo-random function. Once again, perturbed regular gird scheme 192 may be based on any type of regular grid (e.g., square, or hexagonal). A rectangular or hexagonal perturbed grid may be particularly desirable due to the geometric properties of these grid types.

Stochastic sample positioning scheme 194 represents a third potential type of scheme for positioning samples. Stochastic sample positioning involves randomly distributing the samples across a region (e.g., the displayed region on a display device or a particular window). Random positioning of samples may be accomplished through a number of different methods, e.g., using a random number generator such as an internal clock to generate pseudo-random numbers. Random numbers or positions may also be pre-calculated and stored in memory.

Turning now to FIG. 9, details of one embodiment of perturbed regular grid scheme 192 are shown. In this embodiment, samples are randomly offset from a regular square grid by x- and y-offsets. As the enlarged area shows, sample 198 has an x-offset 134 that specifies its horizontal displacement from its corresponding grid intersection point 196. Similarly, sample 198 also has a y-offset 136 that specifies its vertical displacement from grid intersection point 196. The random offset may also be specified by an angle and distance. As with the previously disclosed embodiment that utilized angles and distances, x-offset 134 and y-offset 136 may be limited to a particular minimum and or maximum value or range of values.

Turning now to FIG. 10, details of another embodiment of perturbed regular grid scheme 192 are shown. In this embodiment, the samples are grouped into “bins” 138A-D. In this embodiment, each bin comprises nine (i.e., 3×3) samples. Different bin sizes may be used in other embodiments (e.g., bins storing 2×2 samples or 4×4 samples). In the embodiment shown, each sample's position is determined as an offset relative to the position of the bin. The position of the bins may be defined as any convenient position related to the grid, e.g., the lower left-hand corners 132A-D as shown in the figure. For example, the position of sample 198 is determined by summing x-offset 124 and y-offset 126 to the x and y coordinates of the corner 132D of bin 138D. As previously noted, this may reduce the size of the sample position memory used in some embodiments.

FIG. 11—Converting Samples into Pixels

Turning now to FIG. 11, one possible method for rapidly converting samples stored in sample buffer 162 into pixels is shown. In this embodiment, the contents of sample buffer 162 are organized into columns (e.g., Cols. 1-4). Each column in sample buffer 162 may comprise a two-dimensional array of bins. The columns may be configured to horizontally overlap (e.g., by one or more bins), and each column may be assigned to a particular sample-to-pixel calculation unit 170A-D for the convolution process. The amount of the overlap may depend upon the extent of the filter being used. The example shown in the figure illustrates an overlap of two bins (each square such as square 188 represents a single bin comprising one or more samples). Advantageously, this configuration may allow sample-to-pixel calculation units 170A-D to work independently and in parallel, with each sample-to-pixel calculation unit 170A-D receiving and converting its own column. Overlapping the columns will eliminate visual bands or other artifacts appearing at the column boundaries for any operators larger than a pixel in extent.

Turning now to FIG. 11A, more details of one embodiment of a method for reading the samples from a super-sampled sample buffer are shown. As the figure illustrates, the convolution filter kernel 400 travels across column 414 (see arrow 406) to generate output pixels. One or more sample-to-pixel calculation units 170 may implement the convolution filter kernel 400. A bin cache 408 may used to provide quick access to the samples that may potentially contribute to the output pixel. As the convolution process proceeds, bins are read from the super-sampled sample buffer and stored in bin cache 408. In one embodiment, bins that are no longer needed 410 are overwritten in the cache by new bins 412. As each pixel is generated, convolution filter kernel 400 shifts. Kernel 400 may be visualized as proceeding in a sequential fashion within the column in the direction indicated by arrow 406. When kernel 400 reaches the end of the column, it may shift down one or more rows of samples and then proceed again. Thus the convolution process proceeds in a scan line manner, generating one column of output pixels for display.

Turning now to FIG. 11B, a diagram illustrating potential border conditions is shown. In one embodiment, the bins that fall outside of sample window 420 may be replaced with samples having predetermined background colors specified by the user. In another embodiment, bins that fall outside the window are not used by setting their weighting factors to zero (and then dynamically calculating normalization coefficients). In yet another embodiment, the bins at the inside edge of the window may be duplicated to replace those outside the window. This is indicated by outside bin 430 being replaced by mirror inside bin 432.

FIG. 12—Rendering Sample Pixels into a Super-Sampled Sample Buffer

FIG. 12 is a flowchart of one embodiment of a method for drawing or rendering sample pixels into a super-sampled sample buffer. Certain of the steps of FIG. 12 may occur concurrently or in different orders. In this embodiment, the graphics system receives graphics commands and graphics data from the host CPU 102 or directly from main memory 106 (step 200). Next, the instructions and data are routed to one or more rendering units 150A-D (step 202). If the graphics data is compressed (step 204), then the rendering units 150A-D decompress the data into a useable format, e.g., triangles (step 206). Next, the triangles are processed, e.g., converted to screen space, lit, and transformed (step 208A). If the graphics system implements variable resolution super sampling, then the triangles are compared with the sample density region boundaries (step 208B). In variable-resolution super-sampled sample buffer implementations, different regions of the display device may be allocated different sample densities based upon a number of factors (e.g., the center of the attention on the screen as determined by eye or head tracking). Sample density regions are described in greater detail below (see section entitled Variable Resolution Sample buffer below). If the triangle crosses a region boundary (step 210), then the triangle may be divided into two smaller polygons along the region boundary (step 212). This may allow each newly formed triangle to have a single sample density. In one embodiment, the graphics system may be configured to simply use the entire triangle twice (i.e., once in each region) and then use a bounding box to effectively clip the triangle.

Next, one of the sample position schemes (e.g., regular grid, perturbed regular grid, or stochastic) are selected from the sample position memory 184 (step 214). The sample position scheme will generally have been pre-programmed into the sample position memory 184, but may also be selected “on the fly”. Based upon this sample position scheme and the sample density of the region containing the triangle, rendering units 150A-D determine which bins may contain samples located within the triangle's boundaries (step 216). The offsets for the samples within these bins are then read from sample position memory 184 (step 218). Each sample's position is then calculated using the offsets and is compared with the triangle's vertices to determine if the sample is within the triangle (step 220). Step 220 is discussed in greater detail below.

For each sample that is determined to be within the triangle, the rendering unit draws the sample by calculating the sample's color, alpha and other attributes. This may involve lighting calculation and interpolation based upon the color and texture map information associated with the vertices of the triangle. Once the sample is rendered, it may be forwarded to schedule unit 154, which then stores the sample in sample buffer 162 (step 224).

Note the embodiment of the method described above is used for explanatory purposes only and is not meant to be limiting. For example, in some embodiments the steps shown in the figure as occurring serially may be implemented in parallel. Furthermore, some steps may be reduced or eliminated in certain embodiments of the graphics system (e.g., steps 204-206 in embodiments that do not implement geometry compression or steps 210-212 in embodiments that do not implement a variable resolution super-sampled sample buffer).

Determination of Which Samples Reside Within the Polygon Being Rendered

The comparison of which samples reside within the polygon being rendered may be performed in a number of different ways. In one embodiment, the deltas between the three vertices defining the triangle are first determined. For example, these deltas may be taken in the order of first to second vertex (v2−v1)=d12, second to third vertex (v3−v2)=d23, and third vertex back to the first vertex (v1−v3)=d31. These deltas form vectors, and each vector may be categorized as belonging to one of the four quadrants of the coordinate plane (e.g., by using the two sign bits of its delta X and Y coefficients). A third condition may be added determining whether the vector is an X-major vector or Y-major vector. This may be determined by calculating whether abs(delta_x) is greater than abs(delta_(—y)).

Using these three bits of information, the vectors may each be categorized as belonging to one of eight different regions of the coordinate plane. If three bits are used to define these regions, then the X-sign bit (shifted left by two), the Y-sign bit (shifted left by one), and the X-major bit, may be used to create the eight regions as shown in FIG. 12A.

Next, three edge equations may be used to define the inside portion of the triangle. These edge equations (or half-plane equations) may be defined using slope-intercept form. To reduce the numerical range needed, both X-major and Y-major equation forms may be used (such that the absolute value of the slope value may be in the range of 0 to 1). Thus, the two edge equations are:

X-major: y−m·x−b<0, when the point is below the line

Y-major: x−m·y−b<0, when the point is to the left of the line

The X-major equations produces a negative versus positive value when the point in question is below the line, while the Y-major equation produces a negative versus positive value when the point in question is to the left of the line. Since which side of the line is the “accept” side is known, the sign bit (or the inverse of the sign bit) of the edge equation result may be used to determine whether the sample is on the “accept” side or not. This is referred to herein as the “accept bit”. Thus, a sample is on the accept side of a line if:

X-major: (y−m·x−b<0)<xor>accept

Y-major: (x−m·y−b<0)<xor>accept

The accept bit may be calculated according to the following table, wherein cw designates whether the triangle is clockwise (cw=1) or counter clockwise (cw=0):

1: accept=!cw

0: accept=cw

4: accept=cw

5: accept=cw

7: accept=cw

6: accept=!cw

2: accept=!cw

3: accept=!cw

Tie breaking rules for this representation may also be implemented (e.g., coordinate axes may be defined as belonging to the positive octant). Similarly, X-major may be defined as owning all points that tie on the slopes.

In an alternate embodiment, the accept side of an edge may be determined by applying the edge equation to the third vertex of the triangle (the vertex that is not one of the two vertices forming the edge). This method may incur the additional cost of a multiply-add, which may not be used by the technique described above.

To determine the “faced-ness” of a triangle (i.e., whether the triangle is clockwise or counter-clockwise), the delta-directions of two edges of the triangle may be checked and the slopes of the two edges may be compared. For example, assuming that edge 12 has a delta-direction of 1 and the second edge (edge 23) has a delta-direction of 0, 4, or 5, then the triangle is counter-clockwise. If, however, edge 23 has a delta-direction of 3, 2, or 6, then the triangle is clockwise. If edge 23 has a delta-direction of 1 (i.e., the same as edge 12), then comparing the slopes of the two edges breaks the tie (both are x-major). If edge 12 has a greater slope, then the triangle is counter-clockwise. If edge 23 has a delta-direction of 7 (the exact opposite of edge 12), then again the slopes are compared, but with opposite results in terms of whether the triangle is clockwise or counter-clockwise.

The same analysis can be exhaustively applied to all combinations of edge 12 and edge 23 delta-directions, in every case determining the proper faced-ness. If the slopes are the same in the tie case, then the triangle is degenerate (i.e., with no interior area). It can be explicitly tested for and culled, or, with proper numerical care, it could be let through as it will cause no pixels to render. One special case is when a triangle splits the view plane, but that may be detected earlier in the pipeline (e.g., when front plane and back plane clipping are performed).

Note in most cases only one side of a triangle is rendered. Thus, after the faced-ness of a triangle is determined, if the face is the one to be rejected, then the triangle can be culled (i.e., subject to no further processing with no pixels generated). Further note that this determination of faced-ness only uses one additional comparison (i.e., of the slope of edge 12 to that of edge 23) beyond factors already computed. Many traditional approaches may utilize more complex computation (though at earlier stages of the set-up computation).

FIG. 13—Generating Output Pixels by Selecting and Filtering Samples in the Super-Sampled Sample Buffer

FIG. 13 is a flowchart of one embodiment of a method for selecting and filtering samples stored in the super-sampled sample buffer to generate output pixels. First, a stream of bins are read from the super-sampled sample buffer (step 250). These may be stored in one or more caches to allow the sample-to-pixel calculation units 170 easy access during the convolution process (step 252). Next, the bins are examined to determine which may contain samples that contribute to the output pixel currently being generated by the filter process (step 254). Each sample that is in a bin that may contribute to the output pixel is then individually examined to determine if the sample does indeed contribute (steps 256-258). This determination may be based upon the distance from the sample to the center of the output pixel being generated.

In one embodiment, the sample-to-pixel calculation units 170 may be configured to calculate this distance (i.e., the extent of the filter at sample's position) and then use it to index into a table storing filter weight values according to filter extent (step 260). In another embodiment, however, the potentially expensive calculation for determining the distance from the center of the pixel to the sample (which typically involves a square root function) is avoided by using distance squared to index into the table of filter weights. Alternatively, a function of x and y may be used in lieu of one dependent upon a distance calculation. In one embodiment, this may be accomplished by utilizing a floating point format for the distance (e.g., four or five bits of mantissa and three bits of exponent), thereby allowing much of the accuracy to be maintained while compensating for the increased range in values. In one embodiment, the table may be implemented in ROM. However, RAM tables may also be used. Advantageously, RAM tables may, in some embodiments, allow the graphics system to vary the filter coefficients on a per-frame basis. For example, the filter coefficients may be varied to compensate for known shortcomings of the display or for the user's personal preferences. The graphics system can also vary the filter coefficients on a screen area basis within a frame, or on a per-output pixel basis. Another alternative embodiment may actually calculate the desired filter weights for each sample using specialized hardware (e.g., multipliers and adders). The filter weight for samples outside the limits of the convolution filter may simply be multiplied by a filter weight of zero (step 262), or they may be removed from the calculation entirely.

Once the filter weight for a sample has been determined, the sample may then be multiplied by its filter weight (step 264). The weighted sample may then be summed with a running total to determine the final output pixel's color value (step 266). The filter weight may also be added to a running total pixel filter weight (step 268), which is used to normalize the filtered pixels. Normalization advantageously prevents the filtered pixels (e.g., pixels with more samples than other pixels) from appearing too bright or too dark by compensating for gain introduced by the convolution process. After all the contributing samples have been weighted and summed, the total pixel filter weight may be used to divide out the gain caused by the filtering (step 270). Finally, the normalized output pixel may be output for gamma correction, digital-to-analog conversion (if necessary), and eventual display (step 274).

FIG. 14—Example Output Pixel Convolution

FIG. 14 illustrates a simplified example of an output pixel convolution. As the figure shows, four bins 288A-D contain samples that may possibly contribute to the output pixel. In this example, the center of the output pixel, i.e., the center location where the filter is applied to generate a respective output pixel, is located at the boundary of bins 288A-288D. Each bin comprises sixteen samples, and an array of 2 four bins (2×2) is filtered to generate the output pixel. Assuming circular filters are used, the distance of each sample from the pixel center determines which filter value will be applied to the sample. For example, sample 296 is relatively close to the pixel center, and thus falls within the region of the filter having a filter value of 8. Similarly, samples 294 and 292 fall within the regions of the filter having filter values of 4 and 2, respectively. Sample 290, however, falls outside the maximum filter extent, and thus receives a filter value of 0. Thus sample 290 will not contribute to the output pixel's value. This type of filter ensures that the samples located the closest to the pixel center will contribute the most, while pixels located the far from the pixel center will contribute less to the final output pixel values. This type of filtering automatically performs anti-aliasing by smoothing any abrupt changes in the image (e.g., from a dark line to a light background). Another particularly useful type of filter for anti-aliasing is a windowed sinc filter. Advantageously, the windowed sinc filter contains negative lobes that resharpen some of the blended or “fuzzed” image. Negative lobes are areas where the filter causes the samples to subtract from the pixel being calculated. In contrast samples on either side of the negative lobe add to the pixel being calculated.

Example values for samples 290-296 are illustrated in boxes 300-308. In this example, each sample comprises red, green, blue and alpha values, in addition to the sample's positional data. Block 310 illustrates the calculation of each pixel component value for the non-normalized output pixel. As block 310 indicates, potentially undesirable gain is introduced into the final pixel values (i.e., an out pixel having a red component value of 2000 is much higher than any of the sample's red component values). As previously noted, the filter values may be summed to obtain normalization value 308. Normalization value 308 is used to divide out the unwanted gain from the output pixel. Block 312 illustrates this process and the final normalized example pixel values.

Note the values used herein were chosen for descriptive purposes only and are not meant to be limiting. For example, the filter may have a large number of regions each with a different filter value. In one embodiment, some regions may have negative filter values. The filter utilized may be a continuous function that is evaluated for each sample based on the sample's distance from the pixel center. Also note that floating point values may be used for increased precision. A variety of filters may be utilized, e.g., cylinder, cone, gaussian, Katmull-Rom, windowed sinc, Mitchell filter, box, tent.

Full-Screen Anti-aliasing

The vast majority of current 3D graphics systems only provide real-time anti-aliasing for lines and dots. While some systems also allow the edge of a polygon to be “fuzzed”, this technique typically works best when all polygons have been pre-sorted in depth. This may defeat the purpose of having general-purpose 3D rendering hardware for most applications (which do not depth pre-sort their polygons). In one embodiment, graphics system 112 may be configured to implement full-screen anti-aliasing by stochastically sampling up to sixteen samples per output pixel, filtered by a 4×4-convolution filter.

Dynamic Filter Adjustment for Reduction of Artifacts

The present invention includes an improved system and method for adjusting filtering of samples in generation of output pixels for reduction of artifacts.

The super-sampled frame buffer contains more information than is actually being displayed, i.e., more information than is actually being produced in output pixels in a given frame. As described above, the super-sampled frame buffer stores a plurality of samples which are used to generate output pixels which may be provided directly to the display. The convolution process in generating output pixels in response to samples typically would not use or “throw out” some of the computed sample information. This extra information is rendered or computed in order to detect missing edges and otherwise remove artifacts. However, super-sampling alone may not remove all artifacts, e.g., the various sample position schemes discussed above, such as stochastic sampling or grid-based sampling, may not remove all aliasing and artifacts. For example, performance of 8× super sampling is not a guarantee that all artifacts and aliasing have been removed from the final output image. Rather, stochastic sampling, for example, produces a “trade off” of aliasing for artifacts that appear more like noise, to which the eye is less sensitive. Thus, a graphics system using a super-sampled sample buffer, while better than conventional pixel-based frame buffers, may inadvertently miss some triangles and/or result in some artifacts.

When the render rate is less than the refresh rate, then the samples in the sample buffer may be convolved two or more times, and artifacts may result. As used herein, the term “render rate” refers to the rate at which samples are rendered into the sample buffer. The term “refresh rate” refers to the rate at which the sample to pixel calculation unit operates to select and obtain samples from the sample buffer and filter the samples to generate output pixels which are provided to the display, preferably directly to the display with no frame buffer therebetween.

In one embodiment of the invention, the one or more sample-to-pixel calculation unit(s) 170A-D (referred to in the singular as the “sample-to-pixel calculation unit 170”) is operable to perform convolution at a different rate than, and preferably independent of, the render operation or render rate. Thus, the rate of computing and storing sample data into the sample buffer may be decoupled from the refresh rate or convolve rate. Thus, the sample-to-pixel calculation unit 170 may operate “on-the-fly” independent of the render rate. Where the render rate is less than the refresh rate, some of the same sample data are convolved for two or more consecutive frames, and artifacts may result. Artifacts may also result when the render rate is the same as the refresh rate, but, for example, the sample data currently in the sample buffer is similar to sample data from a prior frame. The present invention includes a system and method for dynamic filter adjustment for reduction of artifacts.

In one embodiment, the sample-to-pixel calculation unit 170 is operable to selectively adjust the filtering of stored samples to reduce artifacts, e.g., is operable to selectively adjust the filtering of stored samples in neighboring frames to reduce artifacts between the neighboring frames. For example, the sample-to-pixel calculation unit 170 may select and filter a first set of stored samples to generate first output pixels for display using a first filter, and may later select and filter a second set of stored samples to generate second output pixels for display using a second filter different than the first filter. This operates to change the artifacts from a fixed position on the display to varying positions on the display, which are more likely to be overlooked by the human visual system.

For example, assume 0.01% of the pixels in a prior frame have an artifact, and the same sample data is being used in a current frame to generate output pixels. In the current frame, the sample-to-pixel calculation unit 170 may operate to shift the center locations where the filter is applied to the sample data by half a pixel in generating output pixels for the current frame. This may completely remove the artifacts for that 0.01% of the pixels in the current frame, with no other artifacts being produced in the current frame. Alternatively, this may completely remove the artifacts for that 0.01% of the pixels in the current frame, but may result in artifacts for other pixels, which will appear in a different position on the display. In this case, the human visual system may average the artifacts, thus producing less perceptible artifacts. Thus the present invention may effectively perform a type of temporal dithering on output pixels, which may result in fewer perceived artifacts.

The sample-to-pixel calculation unit 170 may selectively adjust the filtering of stored samples in neighboring frames by simulation of various screen effects, such as panning and zooming, for reduced artifacts. The sample-to-pixel calculation unit 170 may also selectively adjust the filtering of stored samples in neighboring frames using other pre-determined or stochastic methods, as desired. For example, the sample-to-pixel calculation unit 170 may selectively adjust the filtering of stored samples in neighboring frames by a stochastic value ranging from 0 to 0.5 sub-pixels in either horizontal direction.

The sample-to-pixel calculation unit 170 may utilize a filter in filtering the samples as described above, and the sample-to-pixel calculation unit 170 preferably selectively adjusts center locations where the filter is applied during filtering of stored samples to reduce artifacts. In other words, the sample-to-pixel calculation unit 170 preferably selectively adjusts center locations where the filter is applied relative to the center locations used in a prior frame. The adjustment in center locations where the convolution filter is applied is equivalent to an adjustment in the centers of the output pixels being generated.

The sample-to-pixel calculation unit 170 includes address generator logic for generating addresses corresponding to the center locations of the convolution filter, wherein the address generator logic is programmable to generate addresses at selected sub-pixel positions in the sample buffer corresponding to the desired centers. In the preferred embodiment, the beginning sub-pixel position where the address generator logic begins generating addresses is programmable. The sample-to-pixel calculation unit 170 is operable to selectively adjust the beginning sub-pixel position of the center of the convolution filter in one or more of the x or y direction, and may adjust the center of the convolution filter by a sub-pixel distance relative to the center used in a prior frame. The address generator logic also includes a pixel step size which is programmable, but preferably remains constant. The pixel step size corresponds to a pitch between the pixels, which generally relates to a relative change in the pitch between pixels relative to either a prior pitch or to a selected coordinate system, such as screen space.

In order to implement a filter adjustment, the rendering unit(s) 150 in the graphics system may operate to render additional samples outside of the immediate viewable area so that these samples are available for the desired adjustment. In one embodiment, prior to rendering samples into the sample buffer, the graphics system has already estimated the appearance of the subsequent frame (e.g., has estimated the desired shift in convolution centers). For example, if the desired filter adjustment involves shifting the convolution centers one half pixel to the right, additional samples may be rendered in the sample buffer at locations corresponding to at least one half pixel to the right of the previous viewable area, so that these samples can be used in generating pixels on the right edge of the display. Otherwise, some sample data would be unavailable for the output pixels on the right edge of the display, and undesirable artifacts may result on the right edge of the display. In a similar manner, if the desired filter adjustment involves shifting the convolution centers one half pixel to the left, additional samples may be rendered in the sample buffer at locations corresponding to at least one half pixel to the left of the previous viewable area, so that these samples can be used in generating pixels on the left edge of the display. Where a shift in convolution centers upward or downward is desired, the system may also operate to render additional samples above or below, respectively, the immediate viewable area so that these samples are available for the desired adjustment.

In one embodiment, prior to rendering samples into the sample buffer, the graphics system has already estimated the appearance of the subsequent frame (e.g., has estimated the desired shift in convolution centers), and thus additional samples are rendered into the sample buffer based on this shift estimate. Alternatively, if the additional rendering adds little cost or delay, the rendering units 150 may render additional samples around all edges of the sample buffer, and thus the graphics system can determine the desired shift in convolution centers mid-way through the next frame.

The sample-to-pixel calculation unit 170 may also adjust other parameters, such as the type of filter, the weighting factors used, the radius of the filter, or other filter parameters, to attempt to remove artifacts between successive frames. Where the radius of the filter is adjusted to remove artifacts, blurry portions may “fuzz out” high resolution portions, thereby removing artifacts, but perhaps at the expense of perceived resolution.

Adjustment of Video Timing

The graphics system is also operable to selectively adjust video timing to compensate for the adjustment of the center of the convolution filter during filtering of stored samples. As mentioned above with respect to the discussion of the DACs 178A-B in FIG. 3, when the sample-to-pixel calculation unit 170 horizontally or vertically adjusts the convolution centers in a frame relative to a previous frame as mentioned above, the sample-to-pixel calculation unit 170 also operates to shift or adjust the phase of the pixel clock provided to the DACs 178A-B. This is necessary, due to the adjustment of the convolution centers in a frame relative to a previous frame, to prevent a noticeable “jiggling” of the image. In general, a shift of the convolution centers by a fraction of a pixel directly correlates with a corresponding shift in timing.

The sample-to-pixel calculation unit 170 may operate to horizontally or vertically adjust the convolution centers in a frame. If the convolution centers are vertically shifted by an entire scan line, then the pixels may be delayed by an entire scan line, with the result being a scroll of one scan line in the output of the frame. If a vertical shift is desired in the convolution centers, then this is preferably only performed with an analog display, such as a CRT (cathode ray tube) display, and preferably on sub-line increments such as one half of a line.

The adjusted pixel clock may operate to adjust one or more of the HSYNC signal and the VSYNC signal. In one embodiment, the programmable clock unit 182 includes at least one multiplexer and includes delay elements for generating one or more delayed and advanced versions of the pixel clock. These different versions of the pixel clock are selected based on the type and amount of adjustment to the convolution centers. The programmable clock unit 182 may also operate according to a state machine which controls the video timing.

Note, for some displays, it may be insufficient to simply change one or more of the timing signals provided to the display, such as adjusting the horizontal start pulse, since higher end displays may be able to compensate. Thus the pixel clock provided to the DACs, or other output circuitry, is adjusted.

FIG. 15—Adjustment of Filtering in a Frame

FIG. 15 is a flowchart diagram illustrating operation of the sample-to-pixel calculation unit 170 in adjusting the filtering of samples in a current frame to attempt to remove artifacts, or to generate desired display effects. Here it is presumed that additional samples may have been previously rendered into the sample buffer at locations where the desired adjustment is to occur.

As shown, prior to the beginning of generation of output pixels for a current frame, in step 402 the method programs the starting address of a first convolution center for each sample-to-pixel calculation unit (also called a “convolution pipeline”). Where a single convolution pipeline is used, the method may program the starting address of the convolution center for the upper left pixel that is displayed on the display device. Where multiple convolution pipelines operate in parallel, such as shown in FIG. 11, the method may operate to program the starting address of the convolution center for each respective convolution pipeline, e.g., the convolution center for the upper left starting pixel for each convolution pipeline.

In step 404 the method may program the pixel step value for each convolution pipeline. The pixel step value may include a step value in the horizontal X direction as well as a step value in the vertical Y direction. The pixel step value corresponds to the distance between a convolution center and the next successive convolution center for the adjacent pixel. In one embodiment, the convolution centers for each of the output pixels are determined by the starting address of the convolution center and the respective pixel step value, which may remain constant for an entire frame (or multiple frames).

In one embodiment, the pixel step value remains constant and hence need not be programmed. Assuming a constant pixel step value, a change in the starting address of the convolution center operates to offset the convolution centers for each of the pixels with respect to the convolution centers used for the pixels in the prior frame, wherein the offset is the same for each of the pixels relative to pixels in the prior frame. Thus, in order to adjust the convolution centers consistently for each of the output pixels in a current frame, the method preferably programs a different starting address of the convolution center relative to the prior frame, generally for each convolution pipeline or sample to pixel calculation unit 170, and maintains the same pixel step value as the prior frame. As mentioned, this operates to offset convolution centers for each pixel in the current frame with respect to the convolution centers used for pixels from the prior frame by the same amount.

In another embodiment, the method operates to adjust the pixel step size on a per frame or even per pixel basis, thereby producing varying offsets in the convolution centers for each of the pixels with respect to the convolution centers used for the pixels in the prior frame. For example, the pixel step size may be selectively adjusted on a per pixel basis for each of at least a subset of pixels in the frame, such as by a stochastic adjustment ranging between −0.25 and +0.25 sub-pixels. This may further operate to remove artifacts in certain portions of an image.

Where this method of the present invention is being used to produce display effects such as zooming, the pixel step value may be programmed to a different value relative to the prior frame to implement either a “zoom in” or “zoom out”. For example, the pixel step value is programmed to a smaller step value to zoom in on the image, and is programmed to a larger step value to zoom out of the image. The generation of display effects is discussed further below.

In step 406 the method begins convolution at the starting address programmed in step 402. This involves applying the convolution filter to samples in the sample buffer at the convolution center specified by the starting address in step 402 to generate the first output pixel for display.

In step 408 the method advances to the next convolution center using the step value programmed in step 404.

In step 410 the method performs convolution on samples in the sample buffer at the next convolution center as determined in step 408. This again involves generating an output pixel by applying a convolution filter to samples in the sample buffer based on the convolution center.

As shown, steps 408 and 410 are repeated for each of the output pixels for the respective convolution pipeline. It is also noted that steps 406, 408 and 410 may be performed by each of the respective convolution pipelines or sample to pixel calculation units, if there are more than one, preferably in parallel.

Thus, by simply changing the starting address of the convolution center for each of the one or more sample-to-pixel calculation units or convolution pipelines, the method operates to adjust the convolution centers for each of the output pixels for a current frame relative to the convolution centers used in a prior frame. As described above, this may be performed to attempt to remove artifacts between neighboring frames, such as when the sample data is identical or similar to sample data from a prior frame. This may also be performed to generate various types of display effects as described below.

FIGS. 16 and 17—Example Adjustment of Convolution Centers

FIGS. 16A-16B and 17A and 17B illustrate one example of the operation of the present invention. FIG. 16A illustrates a representative set of samples from the sample buffer, wherein the centers of the convolution filtered are centered around respective bins in the sample buffer. As shown, when the convolution filter is applied using these convolution centers to respective samples to produce output pixels for display, an edge may be produced with an alias or artifact, as shown in FIG. 16B.

FIG. 17A illustrates the same set of sample data wherein the convolution centers have been shifted relative to the convolution filters in FIG. 16A. As shown in FIG. 17A, the convolution centers are shifted to the left by approximately ½ of a pixel. The convolution filters applied at these new convolution centers will generally utilize a different set of samples relative to the convolution filters applied using the convolution centers of FIG. 16A. Thus, although some of the samples may be used in each of the convolution filters of FIGS. 16A and 17A, the shift in convolution centers will result in at least some different samples being used to generate output pixels in FIG. 17A than those used in FIG. 16A

As shown in FIG. 17B, when output pixels are generated in response to the same set of samples, using convolution filters with different or shifted convolution centers as shown in FIG. 17A, the artifact may no longer appear. It is noted that other artifacts may appear in other portions of the image drawn. However, this would typically be less noticeable than situations where the artifact appears in the same position for two or more successive frames.

The present invention may be applied where the sample-to-pixel calculation unit 170 generates output pixels at the same rate as the graphics processor rendering samples to the sample buffer. Where the sample-to-pixel calculation unit 170 generates output pixels at the same rate as the graphics processor rendering samples to the sample buffer, then in general the sample buffer contains new sample data on each refresh of the display.

In this embodiment, the graphics system may receive information from the graphics software driver or the graphics application as to the similarity of sample data in neighboring frames. If one or more of the graphics software driver, the graphics application, or the sample-to-pixel calculation unit determines that the sample data in neighboring frames is sufficiently similar, then the sample-to-pixel calculation unit may operate to adjust the filtering for the current frame of sample data to attempt to remove any artifacts that may appear between the neighboring frames. Stated another way, if one or more of the graphics software driver, the graphics application, or the sample-to-pixel calculation unit determines that the sample data in a current frame is sufficiently similar to sample data from an immediately prior frame, then the sample-to-pixel calculation unit may operate to adjust the filtering for the current frame of sample data to attempt to remove any artifacts that may appear between the neighboring frames.

The determination as to whether sample data is “sufficiently similar” to warrant an adjustment of filtering may involve information received from the application on changes in the camera's nodal point, or may be based on criteria used by the graphics driver.

For example, if a current set of stored samples is determined to be similar or identical to a previous set of stored samples that were previously used in generating output pixels in a previous frame, the sample-to-pixel calculation unit may selectively adjust the filtering of the current set of stored samples in a current frame to reduce artifacts. Stated another way, if a set of stored samples has been previously used in generating first output pixels in a first frame, the sample-to-pixel calculation unit may selectively adjust the filtering of a similar set (or the same set) of stored samples to generate different pixels in a subsequent frame to reduce artifacts. Thus, in situations where the camera's nodal point remains substantially fixed, the present invention operates to subtly vary the camera's nodal point to remove any artifacts that may appear between neighboring frames.

The present invention may also be applied where the sample-to-pixel calculation unit generates output pixels at the same rate as the graphics processor rendering samples to the sample buffer, irregardless of whether the current set of stored samples is determined to be similar or identical to a previous set of stored samples. For example, one or more of the graphics software driver, the graphics application, or the sample-to-pixel calculation unit may operate to adjust the filtering for a current frame of sample data to attempt to remove any artifacts based on other types of criteria, such as the relative closeness of objects in the image to the viewer, or other criteria.

The present invention also comprises a graphics system as described above, wherein the sample-to-pixel calculation unit 170 may operate at a different (e.g., higher) rate than the render rate. Thus, the sample-to-pixel calculation unit 10 may generate output pixels at a different rate than the graphics processor rendering samples to the sample buffer, e.g., the graphics processor is operable to render the plurality of samples to the sample buffer at a first rate, and the sample-to-pixel calculation unit is operable to generate output pixels at a second greater rate. For example, the sample-to-pixel calculation unit may operate at a high refresh rate, e.g., 60 Hz to 84 Hz, and convolve “on-the-fly” at that rate, wherein the render rate may be ½ or ¼ of the convolve rate.

This allows the one or more convolve pipelines or sample-to-pixel calculation units 170 to operate on-the-fly independent of the render rate. In this system, the sample-to-pixel calculation unit 170 is operable to selectively adjust the filtering of stored samples between neighboring frames as described above to reduce artifacts. In other words, where a first set of stored samples is determined to have been previously used in generating output pixels in a first frame, the sample-to-pixel calculation unit is operable to selectively adjust the filtering of the first set of stored samples in a subsequent frame to reduce artifacts. Thus, the samples may be created once, and then convolved two or more times with different filters to remove artifacts, until the graphics processor renders new samples into the sample buffer.

In this embodiment, the graphics system may receive information from the graphics software driver or the graphics application as to whether the same set of sample data is being used in neighboring frames. Alternatively, the rendering unit(s) and/or the sample-to-pixel calculation unit(s) may set / clear one or more bits indicating whether a frame of rendered samples is being re-used to generate output pixels, i.e., a frame of samples used to generate output pixels in a previous frame are also being used to generate output pixels in a subsequent frame. If this condition is detected, the sample-to-pixel calculation unit 170 may be directed to adjust the filtering for the current frame of sample data to attempt to remove any artifacts that may appear between the neighboring frames

Thus, if one or more of the graphics software driver, the graphics application, or the sample-to-pixel calculation unit determines that the same set of sample data is being used to generate output pixels in neighboring frames, then the sample-to-pixel calculation unit 170 may operate to adjust the filtering for the current frame of sample data to attempt to remove any artifacts that may appear between the neighboring frames.

Filter Adjustment to Implement a Display Effect

In another embodiment, the sample-to-pixel calculation unit 170 is operable to adjust filtering of stored samples to implement a display effect. More particularly, the sample-to-pixel calculation unit 170 is operable to selectively adjust the filtering of stored samples in neighboring frames to implement a display effect between the neighboring frames. Thus the method described in FIG. 15 may be used to implement a display effect. The display effect may comprise panning, zooming, rotation, or moving scenes, among others.

In order to properly implement display effects, the rendering unit(s) 150 render the appropriate samples into the sample buffer to ensure that samples are present for the desired display effect, e.g., pan, zoom, rotation, moving scenes, or other operation. This primarily involves rendering samples which may not be immediately displayable due to their being outside of the current displayed area, but which would be used in a pan or zoom effect in a subsequent frame to enable this display effect to operate properly. For example, if a pan to the right is desired, the appropriate number of samples which are positioned to the right of the currently displayed image may be rendered into the sample buffer so that these samples are available to implement the pan effect on the subsequent frame.

Thus, in this embodiment, the sample buffer may store samples corresponding to an area greater then a viewable area of the display, and one or more samples from outside the viewable area of the display may be used to implement the display effect. In the case of a “zoom in”, additional samples outside of the viewable area of the display may not be necessary. For “zoom outs” and pans, the rendering unit(s) preferably render additional samples into the sample buffer in anticipation of these display effects. This would involve computing or rendering an image slightly wider or taller than initially needed, i.e., generating samples outside of the immediate displayable area, wherein the sample-to-pixel convolution unit 170 would operate to implement the display effect for the second convolution cycle on this set of sample data using the additional samples.

In one embodiment, prior to rendering samples into the sample buffer, the graphics system has already estimated the appearance of the subsequent frame (e.g., the desired display effect), and thus has already estimated the desired shift in convolution centers. Thus, the rendering unit 150 preferably knows a priori as to the desired display effect so that the proper samples can be rendered into the sample buffer. This results in only the necessary additional samples being rendered. In another embodiment, the rendering unit 150 may be pre-programmed in a mode to always render a number of samples outside of the currently viewable area in two or more directions, e.g., left, right, top and/or bottom to ensure that samples are necessary to implement any desired effect such as panning left, panning right, panning up, panning down, zooming out, and rotation, among others. Thus, if the additional rendering adds little cost or delay, the rendering units may render additional samples around all edges of the sample buffer, and thus the graphics system can determine the desired display effect, and hence the desired shift in convolution centers, mid-way through the next frame.

The sample-to-pixel calculation unit may adjust filtering by adjusting one or more of the positions (centers) of pixels, the radius of the filter, and the pitch between pixels. The sample-to-pixel calculation unit may also adjust filtering of stored samples to implement the display effect on a fractional-pixel boundary. For example, the sample-to-pixel calculation unit may selectively adjust the filtering of stored samples in neighboring frames to effect panning or zooming between the neighboring frames on a fractional-pixel boundary. When a display effect is implemented on a fractional-pixel boundary, this means that the display effect is not constrained by integer pixel movement, but rather may be implemented by a number of whole and fractional pixels, e.g., a pan to right of 0.25 pixels, 0.5 pixels or 10.25 pixels.

One benefit of this invention is smoother panning or zooming, such as when the samples are being rendered at a lesser rate than the convolve. For example, assume a situation where the camera is panning in a certain direction, or zooming in or out, and the samples are being rendered at half the rate of the convolve operation. In this instance, in the prior art two convolve operations may be performed on the same sample data, and then a jump to the next pan position occurs in the next rendered frame. According to the present invention, the sample-to-pixel calculation unit 170 may operate to adjust the convolution centers (e.g., move the convolution centers 10.5 pixels to the right) in the second convolution cycle on the set of sample data to effect the pan operation, even though new sample data corresponding to the pan has not yet been rendered into the sample buffer. Here it is desirable that additional sample data be initially rendered in the sample buffer at the right of the current viewable area in anticipation of the display effect, which is implemented during the second convolution of the sample data. For example, the rendering unit may render at least an additional 10.5 pixels to the right of the current viewable area to ensure that samples are present to implement the pan to the right by 10.5 pixels.

Thus, if a display effect is desired, and if a first set of stored samples has been previously used in generating output pixels in a first frame, the sample-to-pixel calculation unit 170 is operable to selectively adjust the filtering of the first set of stored samples in a subsequent frame to implement the display effect in the subsequent frame.

FIGS. 18 and 19—Example Adjustment of Convolution Centers and Radius to Implement a Zoom

FIGS. 18 and 19 illustrate an example where the filter adjustment of the present invention may be used to implement a zooming display effect. FIG. 18 illustrates a representative portion of samples from the sample buffer, wherein the convolution centers are centered on respective bins and have a first radius size. FIG. 19 illustrates the filtering applied to a subsequent frame, wherein the same or different sample data may be used, and wherein the convolution center and radius size have been adjusted to implement a “zoom in” effect. As shown in FIG. 19, by changing the center of the convolution filters and the radius of the convolution filters, a different display effect is generated without requiring any new rendering of different sample data into the sample buffer. In other words, the existing samples in the sample buffer can be used in conjunction with a different type of filtering to produce different display effects such as zooming, rotation panning, and moving scenes, among others.

The types of filter variables that can be changed independently include the pitch between pixels, the positions of the pixels, e.g., the convolution centers, and the radius of the filters, among others. The system and method of the present invention may be used to implement these display effects on fractional pixel boundaries, i.e., these effects are not constrained to integer pixel movement, but may be implemented on sub-pixel or fractional pixel boundaries.

It is noted that, in this embodiment, it may not be necessary to adjust the video timing, as the image is actually moving. In another embodiment, the method may adjust the video timing, such as to position a “zoomed in” image on a certain location of the display, or to supplement the change in the convolution centers, as opposed to counteracting the change in the convolution centers.

This method of adjusting filtering to implement a display effect may be used in conjunction with head tracked or eye tracked displays. For example, when a viewer with a head tracked or eye tracked display turns his head rapidly, the method may be implemented on a current set of rendered samples to implement the desired display effect, such as panning, corresponding to the viewer's movement. This may require higher level software, such as the application software or the graphics drivers, e.g., the Java 3D graphics driver, to have knowledge regarding the constraints where these display effects can be implemented, including information such as the minimum clipping distance, the type of movement, and possibly the type of display being used. Thus, the software driver or other graphics software may determine where these display effects can be implemented. If the display effect can be implemented, the method may decompose the movement from one frame to the next and generate interpolation parameters (convolution center shift, filter radius, etc.) for an intermediate frame where the display effect may be implemented using the present invention. This may involve decomposing movement into a combination of a pan and/or a scale to implement the desired effect. For example, the graphics driver, such as a Java 3D graphics driver, would have knowledge regarding the camera position orientation from frame to frame and also have knowledge regarding the graphics environment. If the graphics driver learns that the camera at one frame is at one position and in the next frame is at exactly the same position, with the only difference being a rotation of the camera, then the graphics driver can instruct the graphics system to approximate this by a pan, or by a pan and a scale, through the adjustment of convolution centers or other filter variables.

The desired degree of a pan or rotation to implement a display effect may depend on the relative closeness of the object involved. In one embodiment, the software may calculate the degree of shift based on near and far objects. Where the objects are at infinity or at a constant distance, the degree of shift computed is relatively straightforward. If the objects present on the display have a mixture of distances, then the graphics software may estimate the degree of shift based on an average of selected objects or based on eye tracking information with respect to the convergence of the viewer. As one example, in a simple building walk through, the graphics driver may be preprogrammed or “know” that most objects are relatively close to the viewer and thus this feature can be enabled during the entire walk through. The graphics system and/or software may also determine on a per frame basis the range of distances to determine whether these display effects can be implemented. Where these display effects product too much distortion, either the graphics driver software or the user have the ability to disable this feature. It is noted that this technique may operate best on images which have a focus at a large distance relative to the scale of incremental camera movements. It is further noted that some perspective problems may result for images with a focus at a relatively close distance to the image.

FIG. 20

FIG. 20 is a flowchart diagram illustrating one embodiment of generation of a display effect according to the present invention. As shown, in step 442 the method determines a change in position and orientation of the image being displayed. This step may be performed by graphics driver software executing on the host CPU or by the graphics system 112. In step 444 the method determines a pan and/or scale value based on a specified point in the image using the determined change in position and orientation from step 442. Step 444 may also be performed either by the host CPU or by the graphics system 112. In response to steps 442 and 444, in step 446 the method generates the starting address of the convolution center, step size, and/or filter radius based on the determined pan and scale value from step 444. In step 446 the method may also program other filter variable values to be used to implement the desired pan, scale, rotation or other display effect, as needed.

Although the embodiments above have been described in considerable detail, other versions are possible. Numerous variations and modifications will become apparent to those skilled in the art once the above disclosure is fully appreciated. It is intended that the following claims be interpreted to embrace all such variations and modifications. Note the headings used herein are for organizational purposes only and are not meant to limit the description provided herein or the claims attached hereto. 

What is claimed is:
 1. A graphics system comprising: a graphics processor operable to render a plurality of samples; a sample buffer coupled to said graphics processor for storing said samples; and a sample-to-pixel calculation unit coupled to said sample buffer, wherein the sample-to-pixel calculation unit is operable to select and filter stored samples to generate output pixels for display; wherein the sample-to-pixel calculation unit is operable to adjust filtering of stored samples to implement a display effect.
 2. The graphics system of claim 1, wherein the sample-to-pixel calculation unit is operable to selectively adjust the filtering of stored samples in neighboring frames to implement a display effect between said neighboring frames.
 3. The graphics system of claim 1, wherein said sample-to-pixel calculation unit is operable to select and filter a first set of stored samples to generate first output pixels for display using a first filter; wherein said sample-to-pixel calculation unit is operable to select and filter a second set of stored samples to generate second output pixels for display using a second filter different than said first filter.
 4. The graphics system of claim 1, wherein the display effect comprises one of: panning, zooming, rotation, and moving scenes.
 5. The graphics system of claim 1, wherein the sample-to-pixel calculation unit is operable to adjust filtering by adjusting one or more of: position of pixels, radius of the filter, and pitch between pixels.
 6. The graphics system of claim 1, wherein the sample-to-pixel calculation unit is operable to selectively adjust the filtering of stored samples in neighboring frames to effect panning between said neighboring frames.
 7. The graphics system of claim 1, wherein the sample-to-pixel calculation unit is operable to selectively adjust the filtering of stored samples in neighboring frames to effect zooming between said neighboring frames.
 8. The graphics system of claim 1, wherein the sample-to-pixel calculation unit is operable to adjust filtering of stored samples to implement the display effect on a fractional-pixel boundary.
 9. The graphics system of claim 1, wherein the sample-to-pixel calculation unit is operable to selectively adjust the filtering of stored samples in neighboring frames to effect panning between said neighboring frames on a fractional-pixel boundary.
 10. The graphics system of claim 1, wherein the sample-to-pixel calculation unit is operable to selectively adjust the filtering of stored samples in neighboring frames to effect zooming between said neighboring frames on a fractional-pixel boundary.
 11. The graphics system of claim 1, wherein the graphics processor is operable to render the plurality of samples to the sample buffer at a first rate; and wherein the sample-to-pixel calculation unit is operable to generate output pixels at a second greater rate; wherein, if a display effect is desired, and if a first set of stored samples has been previously used in generating output pixels in a first frame, the sample-to-pixel calculation unit is operable to selectively adjust the filtering of said first set of stored samples in a subsequent frame to implement the display effect in the subsequent frame.
 12. The graphics system of claim 1, wherein the graphics system includes a display; wherein the sample buffer stores samples corresponding to an area greater then a viewable area of the display; wherein one or more samples from outside the viewable area of the display in a prior frame are used to implement the display effect in a current frame.
 13. The graphics system of claim 1, wherein the sample-to-pixel calculation unit utilizes a filter in filtering the samples; wherein the sample-to-pixel calculation unit is operable to selectively adjust center locations of the filter during filtering of stored samples to implement the display effect.
 14. The graphics system of claim 13, wherein the graphics system is operable to selectively adjust video timing to compensate for the selective adjustment of the center locations.
 15. The graphics system of claim 13, wherein the sample-to-pixel calculation unit is operable to selectively adjust the center locations in one or more of the x or y direction.
 16. The graphics system of claim 13, wherein the sample-to-pixel calculation unit is operable to selectively adjust the center locations by a sub-pixel distance relative to center locations used in a prior frame.
 17. The graphics system of claim 13, wherein the sample-to-pixel calculation unit utilizes a convolution filter in filtering the samples.
 18. The graphics system of claim 1, wherein the sample-to-pixel calculation unit is operable to select and filter stored samples and generate output pixels which are provided directly to a display with no frame buffer therebetween.
 19. The graphics system of claim 1, wherein said sample-to-pixel calculation unit is configured to select and filter samples to form output pixels on a real time basis.
 20. The graphics system of claim 1, wherein said sample-to-pixel calculation unit is configured to select and filter samples to form output pixels on an on-the-fly basis.
 21. A method for generating pixels for display in a graphics system, the method comprising: rendering a plurality of samples into a sample buffer; generating output pixels in response to the plurality of samples stored in the sample buffer, wherein said generating includes selecting and filtering stored samples to generate output pixels for display; wherein said generating output pixels includes selectively adjusting the filtering of stored samples to implement a display effect.
 22. The method of claim 21, wherein said generating output pixels includes selectively adjusting the filtering of stored samples in neighboring frames to implement a display effect between said neighboring frames.
 23. The method of claim 21, wherein said generating output pixels includes: selecting and filtering a first set of stored samples to generate first output pixels for display using a first filter; selecting and filtering a second set of stored samples to generate second output pixels for display using a second filter different than said first filter.
 24. The method of claim 21, wherein the display effect comprises one of: panning, zooming, rotation, and moving scenes.
 25. The method of claim 21, wherein said generating output pixels includes selectively adjusting the filtering of stored samples to adjust filtering by adjusting one or more of: position of pixels, radius of the filter, and pitch between pixels.
 26. The method of claim 21, wherein said generating output pixels includes selectively adjusting the filtering of stored samples in neighboring frames to effect panning between said neighboring frames.
 27. The method of claim 21, wherein said generating output pixels includes selectively adjusting the filtering of stored samples in neighboring frames to effect zooming between said neighboring frames.
 28. The method of claim 21, wherein said generating output pixels includes adjusting filtering of stored samples to implement the display effect on a fractional-pixel boundary.
 29. The method of claim 21, wherein said generating output pixels includes adjusting filtering of stored samples in neighboring frames to effect panning between said neighboring frames on a fractional-pixel boundary.
 30. The method of claim 21, wherein said generating output pixels includes adjusting filtering of stored samples in neighboring frames to effect zooming between said neighboring frames on a fractional-pixel boundary.
 31. The method of claim 21, wherein said rendering the plurality of samples occurs at a first rate; and wherein said generating output pixels occurs at a second greater rate; wherein, if a first set of stored samples has been previously used in generating output pixels in a first frame, said generating includes selectively adjusting the filtering of said first set of stored samples in a subsequent frame to implement the display effect in the subsequent frame.
 32. The method of claim 21, wherein said rendering includes rendering samples into the sample buffer corresponding to an area greater then a viewable area of a display; wherein one or more samples from outside the viewable area of the display in a prior frame are used to implement the display effect in a current frame.
 33. The method of claim 21, wherein said generating output pixels utilizes a filter in filtering the samples; wherein said generating output pixels includes selectively adjusting a center of the filter during filtering of stored samples to implement the display effect.
 34. The method of claim 33, further comprising: selectively adjusting video timing to compensate for the selective adjustment of the center locations.
 35. The method of claim 33, wherein said selectively adjusting includes selectively adjusting the center locations in one or more of the x or y direction.
 36. The method of claim 33, wherein said selectively adjusting includes selectively adjusting the center locations by a sub-pixel distance relative to center locations used in a prior frame.
 37. The method of claim 33, wherein said generating output pixels utilizes a convolution filter in filtering the samples.
 38. The method of claim 21, wherein said generating comprises selecting and filtering stored samples to generate output pixels which are provided directly to a display with no frame buffer therebetween.
 39. The method of claim 21, wherein said generating comprises selecting and filtering stored samples to form output pixels on a real time basis.
 40. The method of claim 21, wherein said generating comprises selecting and filtering stored samples to form output pixels on an on-the-fly basis. 